Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(boosting). Showing records 1 – 30 of 223 total matches.

[1] [2] [3] [4] [5] [6] [7] [8]

Search Limiters

Last 2 Years | English Only

Degrees

Levels

Languages

Country

▼ Search Limiters


Università della Svizzera italiana

1. Colangelo, Dominik. Semi-parametric implied volatility surface models and forecasts based on a regression tree-boosting algorithm.

Degree: 2009, Università della Svizzera italiana

 A new methodology for semi-parametric modelling of implied volatility surfaces is presented. This methodology is dependent upon the development of a feasible estimating strategy in… (more)

Subjects/Keywords: Boosting

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Colangelo, D. (2009). Semi-parametric implied volatility surface models and forecasts based on a regression tree-boosting algorithm. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/17184

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Colangelo, Dominik. “Semi-parametric implied volatility surface models and forecasts based on a regression tree-boosting algorithm.” 2009. Thesis, Università della Svizzera italiana. Accessed December 04, 2020. http://doc.rero.ch/record/17184.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Colangelo, Dominik. “Semi-parametric implied volatility surface models and forecasts based on a regression tree-boosting algorithm.” 2009. Web. 04 Dec 2020.

Vancouver:

Colangelo D. Semi-parametric implied volatility surface models and forecasts based on a regression tree-boosting algorithm. [Internet] [Thesis]. Università della Svizzera italiana; 2009. [cited 2020 Dec 04]. Available from: http://doc.rero.ch/record/17184.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Colangelo D. Semi-parametric implied volatility surface models and forecasts based on a regression tree-boosting algorithm. [Thesis]. Università della Svizzera italiana; 2009. Available from: http://doc.rero.ch/record/17184

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Rochester Institute of Technology

2. Reuter, Steven Paul. LVAD Occlusion Condition Monitoring Using Boost Classification Trees.

Degree: MS, Mechanical Engineering, 2019, Rochester Institute of Technology

  Cardiac related diseases are a serious health risk for adults. Consequently, therapies exist to treat these aliments such as heart transplant and medication. Heart… (more)

Subjects/Keywords: Boosting; Condition; LVAD; Monitoring

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Reuter, S. P. (2019). LVAD Occlusion Condition Monitoring Using Boost Classification Trees. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10243

Chicago Manual of Style (16th Edition):

Reuter, Steven Paul. “LVAD Occlusion Condition Monitoring Using Boost Classification Trees.” 2019. Masters Thesis, Rochester Institute of Technology. Accessed December 04, 2020. https://scholarworks.rit.edu/theses/10243.

MLA Handbook (7th Edition):

Reuter, Steven Paul. “LVAD Occlusion Condition Monitoring Using Boost Classification Trees.” 2019. Web. 04 Dec 2020.

Vancouver:

Reuter SP. LVAD Occlusion Condition Monitoring Using Boost Classification Trees. [Internet] [Masters thesis]. Rochester Institute of Technology; 2019. [cited 2020 Dec 04]. Available from: https://scholarworks.rit.edu/theses/10243.

Council of Science Editors:

Reuter SP. LVAD Occlusion Condition Monitoring Using Boost Classification Trees. [Masters Thesis]. Rochester Institute of Technology; 2019. Available from: https://scholarworks.rit.edu/theses/10243


California State University – Sacramento

3. Yadkikar, Pallavi Rajendra. GPU based malware prediction using LightGBM and XGBoost.

Degree: MS, Computer Science, 2020, California State University – Sacramento

 The malware industry is a billion-dollar market that aims to evade conventional security measures. Once the system is breached, it gets highly vulnerable to all… (more)

Subjects/Keywords: artifitial intelligence; gradient; boosting

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Yadkikar, P. R. (2020). GPU based malware prediction using LightGBM and XGBoost. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/216939

Chicago Manual of Style (16th Edition):

Yadkikar, Pallavi Rajendra. “GPU based malware prediction using LightGBM and XGBoost.” 2020. Masters Thesis, California State University – Sacramento. Accessed December 04, 2020. http://hdl.handle.net/10211.3/216939.

MLA Handbook (7th Edition):

Yadkikar, Pallavi Rajendra. “GPU based malware prediction using LightGBM and XGBoost.” 2020. Web. 04 Dec 2020.

Vancouver:

Yadkikar PR. GPU based malware prediction using LightGBM and XGBoost. [Internet] [Masters thesis]. California State University – Sacramento; 2020. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/10211.3/216939.

Council of Science Editors:

Yadkikar PR. GPU based malware prediction using LightGBM and XGBoost. [Masters Thesis]. California State University – Sacramento; 2020. Available from: http://hdl.handle.net/10211.3/216939


Hong Kong University of Science and Technology

4. Ye, Yushi. Numerical study on ensemble learning.

Degree: 2016, Hong Kong University of Science and Technology

 Ensemble learning is a class of learning algorithms which tries to mix a set of base learners (or hypotheses) and aggregate their decisions together. Compared… (more)

Subjects/Keywords: Machine learning ; Boosting (Algorithms)

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ye, Y. (2016). Numerical study on ensemble learning. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-89132 ; https://doi.org/10.14711/thesis-b1627122 ; http://repository.ust.hk/ir/bitstream/1783.1-89132/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ye, Yushi. “Numerical study on ensemble learning.” 2016. Thesis, Hong Kong University of Science and Technology. Accessed December 04, 2020. http://repository.ust.hk/ir/Record/1783.1-89132 ; https://doi.org/10.14711/thesis-b1627122 ; http://repository.ust.hk/ir/bitstream/1783.1-89132/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ye, Yushi. “Numerical study on ensemble learning.” 2016. Web. 04 Dec 2020.

Vancouver:

Ye Y. Numerical study on ensemble learning. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2016. [cited 2020 Dec 04]. Available from: http://repository.ust.hk/ir/Record/1783.1-89132 ; https://doi.org/10.14711/thesis-b1627122 ; http://repository.ust.hk/ir/bitstream/1783.1-89132/1/th_redirect.html.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ye Y. Numerical study on ensemble learning. [Thesis]. Hong Kong University of Science and Technology; 2016. Available from: http://repository.ust.hk/ir/Record/1783.1-89132 ; https://doi.org/10.14711/thesis-b1627122 ; http://repository.ust.hk/ir/bitstream/1783.1-89132/1/th_redirect.html

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Hong Kong

5. 董凤娇. Improving discrete AdaBoost for classification by randomization methods.

Degree: 2016, University of Hong Kong

 Adaboost, a typical boosting method for classification, performs well in classification problems. Many researchers have applied different types of randomization techniques to Adaboost for further… (more)

Subjects/Keywords: Boosting (Algorithms)

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

董凤娇. (2016). Improving discrete AdaBoost for classification by randomization methods. (Thesis). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/226781

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

董凤娇. “Improving discrete AdaBoost for classification by randomization methods.” 2016. Thesis, University of Hong Kong. Accessed December 04, 2020. http://hdl.handle.net/10722/226781.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

董凤娇. “Improving discrete AdaBoost for classification by randomization methods.” 2016. Web. 04 Dec 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

董凤娇. Improving discrete AdaBoost for classification by randomization methods. [Internet] [Thesis]. University of Hong Kong; 2016. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/10722/226781.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

董凤娇. Improving discrete AdaBoost for classification by randomization methods. [Thesis]. University of Hong Kong; 2016. Available from: http://hdl.handle.net/10722/226781

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete
Not specified: Masters Thesis or Doctoral Dissertation


Princeton University

6. Mukherjee, Indraneel. Game theory and optimization in boosting .

Degree: PhD, 2011, Princeton University

Boosting is a central technique of machine learning, the branch of artificial intelligence concerned with designing computer programs that can build increasingly better models of… (more)

Subjects/Keywords: boosting; game theory; optimization

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mukherjee, I. (2011). Game theory and optimization in boosting . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01dv13zt22m

Chicago Manual of Style (16th Edition):

Mukherjee, Indraneel. “Game theory and optimization in boosting .” 2011. Doctoral Dissertation, Princeton University. Accessed December 04, 2020. http://arks.princeton.edu/ark:/88435/dsp01dv13zt22m.

MLA Handbook (7th Edition):

Mukherjee, Indraneel. “Game theory and optimization in boosting .” 2011. Web. 04 Dec 2020.

Vancouver:

Mukherjee I. Game theory and optimization in boosting . [Internet] [Doctoral dissertation]. Princeton University; 2011. [cited 2020 Dec 04]. Available from: http://arks.princeton.edu/ark:/88435/dsp01dv13zt22m.

Council of Science Editors:

Mukherjee I. Game theory and optimization in boosting . [Doctoral Dissertation]. Princeton University; 2011. Available from: http://arks.princeton.edu/ark:/88435/dsp01dv13zt22m


Tampere University

7. PAUKKERI, RAUNO. Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa .

Degree: 2013, Tampere University

 Tämän tutkielman tarkoituksena on selvittää ja vertailla erilaisia tilastollisia oppimisyhdistelmiä erään suomalaisen teleoperaattorin asiakasvaihtuvuuden ennustamisessa. Tutkielmassa tarkastellaan myös, onko opetusaineiston painottamisella vaikutusta asiakasvaihtuvuuden ennustamisen tarkkuuteen.… (more)

Subjects/Keywords: Bagging; Boosting; Real AdaBoost; Gradient Boosting; satunnaismetsä; päätöspuut

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

PAUKKERI, R. (2013). Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/94855

Chicago Manual of Style (16th Edition):

PAUKKERI, RAUNO. “Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa .” 2013. Masters Thesis, Tampere University. Accessed December 04, 2020. https://trepo.tuni.fi/handle/10024/94855.

MLA Handbook (7th Edition):

PAUKKERI, RAUNO. “Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa .” 2013. Web. 04 Dec 2020.

Vancouver:

PAUKKERI R. Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa . [Internet] [Masters thesis]. Tampere University; 2013. [cited 2020 Dec 04]. Available from: https://trepo.tuni.fi/handle/10024/94855.

Council of Science Editors:

PAUKKERI R. Tilastolliset oppimisyhdistelmät asiakasvaihtuvuuden ennustamisessa . [Masters Thesis]. Tampere University; 2013. Available from: https://trepo.tuni.fi/handle/10024/94855


University of Namibia

8. Haufiku, Naftal K. An examination of hedging and boosting devices used in academic discourse: case of 2014 and 2015 master of Arts in English Studies thesis at the University of Namibia .

Degree: 2016, University of Namibia

 Hedges and boosters play different roles in academic discourse. This thesis is an analysis of the application of hedges and boosters in all ten theses… (more)

Subjects/Keywords: Hedging devices ; Boosting devices ; Academic discourse

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Haufiku, N. K. (2016). An examination of hedging and boosting devices used in academic discourse: case of 2014 and 2015 master of Arts in English Studies thesis at the University of Namibia . (Thesis). University of Namibia. Retrieved from http://hdl.handle.net/11070/1935

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Haufiku, Naftal K. “An examination of hedging and boosting devices used in academic discourse: case of 2014 and 2015 master of Arts in English Studies thesis at the University of Namibia .” 2016. Thesis, University of Namibia. Accessed December 04, 2020. http://hdl.handle.net/11070/1935.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Haufiku, Naftal K. “An examination of hedging and boosting devices used in academic discourse: case of 2014 and 2015 master of Arts in English Studies thesis at the University of Namibia .” 2016. Web. 04 Dec 2020.

Vancouver:

Haufiku NK. An examination of hedging and boosting devices used in academic discourse: case of 2014 and 2015 master of Arts in English Studies thesis at the University of Namibia . [Internet] [Thesis]. University of Namibia; 2016. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/11070/1935.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Haufiku NK. An examination of hedging and boosting devices used in academic discourse: case of 2014 and 2015 master of Arts in English Studies thesis at the University of Namibia . [Thesis]. University of Namibia; 2016. Available from: http://hdl.handle.net/11070/1935

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brunel University

9. Zhang, Yan. Experimental investigation of CAI combustion in a two-stroke poppet valve DI engine.

Degree: PhD, 2015, Brunel University

 Due to their ability to simultaneously reduce fuel consumption and NOx emissions, Controlled Auto Ignition (CAI) and HCCI combustion processes have been extensively researched over… (more)

Subjects/Keywords: 621.43; Two/four-stroke; Scavenging; Boosting; Ethanol

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, Y. (2015). Experimental investigation of CAI combustion in a two-stroke poppet valve DI engine. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/10531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642456

Chicago Manual of Style (16th Edition):

Zhang, Yan. “Experimental investigation of CAI combustion in a two-stroke poppet valve DI engine.” 2015. Doctoral Dissertation, Brunel University. Accessed December 04, 2020. http://bura.brunel.ac.uk/handle/2438/10531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642456.

MLA Handbook (7th Edition):

Zhang, Yan. “Experimental investigation of CAI combustion in a two-stroke poppet valve DI engine.” 2015. Web. 04 Dec 2020.

Vancouver:

Zhang Y. Experimental investigation of CAI combustion in a two-stroke poppet valve DI engine. [Internet] [Doctoral dissertation]. Brunel University; 2015. [cited 2020 Dec 04]. Available from: http://bura.brunel.ac.uk/handle/2438/10531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642456.

Council of Science Editors:

Zhang Y. Experimental investigation of CAI combustion in a two-stroke poppet valve DI engine. [Doctoral Dissertation]. Brunel University; 2015. Available from: http://bura.brunel.ac.uk/handle/2438/10531 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642456


KTH

10. Sarainmaa, Olli. Large Efficient Maritime Propeller without Hull Pressure Excitations.

Degree: Naval Systems, 2018, KTH

This thesis studies competence of simplified simulation methods for boosting simulation.  The most efficient propulsion unit has higher amount of power compared to less… (more)

Subjects/Keywords: CFD; propulsion; concept; boosting; Vehicle Engineering; Farkostteknik

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sarainmaa, O. (2018). Large Efficient Maritime Propeller without Hull Pressure Excitations. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239628

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sarainmaa, Olli. “Large Efficient Maritime Propeller without Hull Pressure Excitations.” 2018. Thesis, KTH. Accessed December 04, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239628.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sarainmaa, Olli. “Large Efficient Maritime Propeller without Hull Pressure Excitations.” 2018. Web. 04 Dec 2020.

Vancouver:

Sarainmaa O. Large Efficient Maritime Propeller without Hull Pressure Excitations. [Internet] [Thesis]. KTH; 2018. [cited 2020 Dec 04]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239628.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sarainmaa O. Large Efficient Maritime Propeller without Hull Pressure Excitations. [Thesis]. KTH; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239628

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Princeton University

11. Luo, Haipeng. Optimal and Adaptive Online Learning .

Degree: PhD, 2016, Princeton University

 Online learning is one of the most important and well-established machine learning models. Generally speaking, the goal of online learning is to make a sequence… (more)

Subjects/Keywords: boosting; machine learning; online learning; optimization; prediction

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Luo, H. (2016). Optimal and Adaptive Online Learning . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01qz20sv914

Chicago Manual of Style (16th Edition):

Luo, Haipeng. “Optimal and Adaptive Online Learning .” 2016. Doctoral Dissertation, Princeton University. Accessed December 04, 2020. http://arks.princeton.edu/ark:/88435/dsp01qz20sv914.

MLA Handbook (7th Edition):

Luo, Haipeng. “Optimal and Adaptive Online Learning .” 2016. Web. 04 Dec 2020.

Vancouver:

Luo H. Optimal and Adaptive Online Learning . [Internet] [Doctoral dissertation]. Princeton University; 2016. [cited 2020 Dec 04]. Available from: http://arks.princeton.edu/ark:/88435/dsp01qz20sv914.

Council of Science Editors:

Luo H. Optimal and Adaptive Online Learning . [Doctoral Dissertation]. Princeton University; 2016. Available from: http://arks.princeton.edu/ark:/88435/dsp01qz20sv914


Rochester Institute of Technology

12. Houston, Paige. An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error.

Degree: MS, School of Mathematical Sciences (COS), 2016, Rochester Institute of Technology

  Statistical machine learning uses data to model a relationship between many parameters, or explanatory variables, and a response variable. The adaptive boosting algorithm is… (more)

Subjects/Keywords: Adaptive boosting; Boosting; Generalized error; Statistical machine learning; Test error upper bound

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Houston, P. (2016). An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9191

Chicago Manual of Style (16th Edition):

Houston, Paige. “An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error.” 2016. Masters Thesis, Rochester Institute of Technology. Accessed December 04, 2020. https://scholarworks.rit.edu/theses/9191.

MLA Handbook (7th Edition):

Houston, Paige. “An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error.” 2016. Web. 04 Dec 2020.

Vancouver:

Houston P. An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error. [Internet] [Masters thesis]. Rochester Institute of Technology; 2016. [cited 2020 Dec 04]. Available from: https://scholarworks.rit.edu/theses/9191.

Council of Science Editors:

Houston P. An Empirical Demonstration of the Probabilistic Upper Bound of the Adaptive Boosting Test Error. [Masters Thesis]. Rochester Institute of Technology; 2016. Available from: https://scholarworks.rit.edu/theses/9191


Universidade Presbiteriana Mackenzie

13. Vânia Rosatti de Siqueira. Um modelo de credit scoring para microcrédito: uma inovação no mercado brasileiro.

Degree: 2011, Universidade Presbiteriana Mackenzie

As experiências do Grameen Bank com operações de microcrédito têm sido reproduzidas em vários países, principalmente as relacionadas com as duas grandes inovações neste mercado:… (more)

Subjects/Keywords: microcrédito; credit scoring; inovação; bagging; boosting; microcredit; credit scoring; innovation; bagging; boosting; ADMINISTRACAO DE EMPRESAS

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Siqueira, V. R. d. (2011). Um modelo de credit scoring para microcrédito: uma inovação no mercado brasileiro. (Thesis). Universidade Presbiteriana Mackenzie. Retrieved from http://tede.mackenzie.com.br//tde_busca/arquivo.php?codArquivo=2434

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Siqueira, Vânia Rosatti de. “Um modelo de credit scoring para microcrédito: uma inovação no mercado brasileiro.” 2011. Thesis, Universidade Presbiteriana Mackenzie. Accessed December 04, 2020. http://tede.mackenzie.com.br//tde_busca/arquivo.php?codArquivo=2434.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Siqueira, Vânia Rosatti de. “Um modelo de credit scoring para microcrédito: uma inovação no mercado brasileiro.” 2011. Web. 04 Dec 2020.

Vancouver:

Siqueira VRd. Um modelo de credit scoring para microcrédito: uma inovação no mercado brasileiro. [Internet] [Thesis]. Universidade Presbiteriana Mackenzie; 2011. [cited 2020 Dec 04]. Available from: http://tede.mackenzie.com.br//tde_busca/arquivo.php?codArquivo=2434.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Siqueira VRd. Um modelo de credit scoring para microcrédito: uma inovação no mercado brasileiro. [Thesis]. Universidade Presbiteriana Mackenzie; 2011. Available from: http://tede.mackenzie.com.br//tde_busca/arquivo.php?codArquivo=2434

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

14. Pisetta, Vincent. New Insights into Decision Trees Ensembles : Nouveaux apports dans l'apprentissage par ensembles d'arbres.

Degree: Docteur es, Informatique, 2012, Université Lumière – Lyon II

Les ensembles d’arbres constituent à l’heure actuelle l’une des méthodes d’apprentissage statistique les plus performantes. Toutefois, leurs propriétés théoriques, ainsi que leurs performances empiriques restent… (more)

Subjects/Keywords: Méthodes ensemblistes; Boosting; Forêts aléatoires; Discrimination Stochastique; Ensemble methods; Boosting; Random Forests; Stochastic Discrimination

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pisetta, V. (2012). New Insights into Decision Trees Ensembles : Nouveaux apports dans l'apprentissage par ensembles d'arbres. (Doctoral Dissertation). Université Lumière – Lyon II. Retrieved from http://www.theses.fr/2012LYO20018

Chicago Manual of Style (16th Edition):

Pisetta, Vincent. “New Insights into Decision Trees Ensembles : Nouveaux apports dans l'apprentissage par ensembles d'arbres.” 2012. Doctoral Dissertation, Université Lumière – Lyon II. Accessed December 04, 2020. http://www.theses.fr/2012LYO20018.

MLA Handbook (7th Edition):

Pisetta, Vincent. “New Insights into Decision Trees Ensembles : Nouveaux apports dans l'apprentissage par ensembles d'arbres.” 2012. Web. 04 Dec 2020.

Vancouver:

Pisetta V. New Insights into Decision Trees Ensembles : Nouveaux apports dans l'apprentissage par ensembles d'arbres. [Internet] [Doctoral dissertation]. Université Lumière – Lyon II; 2012. [cited 2020 Dec 04]. Available from: http://www.theses.fr/2012LYO20018.

Council of Science Editors:

Pisetta V. New Insights into Decision Trees Ensembles : Nouveaux apports dans l'apprentissage par ensembles d'arbres. [Doctoral Dissertation]. Université Lumière – Lyon II; 2012. Available from: http://www.theses.fr/2012LYO20018

15. Lechervy, Alexis. Apprentissage interactif et multi-classes pour la détection de concepts sémantiques dans les données multimédia : Interactive and multi-class Learning to detect semantic concepts in the multimedia data.

Degree: Docteur es, STIC (sciences et technologies de l'information et de la communication) - Cergy, 2012, Cergy-Pontoise

Récemment les techniques d'apprentissage automatique ont montré leurs capacité à identifier des catégories d'images à partir de descripteurs extrait de caractéristiques visuels des images. Face… (more)

Subjects/Keywords: Apprentissage; Interactif; Multi-classe; Boosting; Kernel; Learning; Interactive; Multi-class; Boosting; Kernel

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lechervy, A. (2012). Apprentissage interactif et multi-classes pour la détection de concepts sémantiques dans les données multimédia : Interactive and multi-class Learning to detect semantic concepts in the multimedia data. (Doctoral Dissertation). Cergy-Pontoise. Retrieved from http://www.theses.fr/2012CERG0581

Chicago Manual of Style (16th Edition):

Lechervy, Alexis. “Apprentissage interactif et multi-classes pour la détection de concepts sémantiques dans les données multimédia : Interactive and multi-class Learning to detect semantic concepts in the multimedia data.” 2012. Doctoral Dissertation, Cergy-Pontoise. Accessed December 04, 2020. http://www.theses.fr/2012CERG0581.

MLA Handbook (7th Edition):

Lechervy, Alexis. “Apprentissage interactif et multi-classes pour la détection de concepts sémantiques dans les données multimédia : Interactive and multi-class Learning to detect semantic concepts in the multimedia data.” 2012. Web. 04 Dec 2020.

Vancouver:

Lechervy A. Apprentissage interactif et multi-classes pour la détection de concepts sémantiques dans les données multimédia : Interactive and multi-class Learning to detect semantic concepts in the multimedia data. [Internet] [Doctoral dissertation]. Cergy-Pontoise; 2012. [cited 2020 Dec 04]. Available from: http://www.theses.fr/2012CERG0581.

Council of Science Editors:

Lechervy A. Apprentissage interactif et multi-classes pour la détection de concepts sémantiques dans les données multimédia : Interactive and multi-class Learning to detect semantic concepts in the multimedia data. [Doctoral Dissertation]. Cergy-Pontoise; 2012. Available from: http://www.theses.fr/2012CERG0581


University of Cincinnati

16. Dinger, Steven. Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models.

Degree: PhD, Business: Business Administration, 2019, University of Cincinnati

 Reinforcement learning has become a popular research topic due to the recent successes in combining deep learning value function estimation and reinforcement learning. Because of… (more)

Subjects/Keywords: Statistics; Fitted Q-Iteration; Gradient Boosting; Online Random Forest; Q-Learning; Twin Boosting; Variable Selection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Dinger, S. (2019). Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035

Chicago Manual of Style (16th Edition):

Dinger, Steven. “Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models.” 2019. Doctoral Dissertation, University of Cincinnati. Accessed December 04, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035.

MLA Handbook (7th Edition):

Dinger, Steven. “Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models.” 2019. Web. 04 Dec 2020.

Vancouver:

Dinger S. Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models. [Internet] [Doctoral dissertation]. University of Cincinnati; 2019. [cited 2020 Dec 04]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035.

Council of Science Editors:

Dinger S. Essays on Reinforcement Learning with Decision Trees and Accelerated Boosting of Partially Linear Additive Models. [Doctoral Dissertation]. University of Cincinnati; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1562923541849035

17. Llerena, Nils Ever Murrugarra. Ensembles na classificação relacional.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2011, University of São Paulo

Em diversos domínios, além das informações sobre os objetos ou entidades que os compõem, existem, também, informaçõoes a respeito das relações entre esses objetos. Alguns… (more)

Subjects/Keywords: Aprendizado de máquina; Bagging; Bagging; Boosting; Boosting; Classificadores baseados em grafos; Ensembles; Ensembles; Graph-based classifiers; Machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Llerena, N. E. M. (2011). Ensembles na classificação relacional. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102011-095113/ ;

Chicago Manual of Style (16th Edition):

Llerena, Nils Ever Murrugarra. “Ensembles na classificação relacional.” 2011. Masters Thesis, University of São Paulo. Accessed December 04, 2020. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102011-095113/ ;.

MLA Handbook (7th Edition):

Llerena, Nils Ever Murrugarra. “Ensembles na classificação relacional.” 2011. Web. 04 Dec 2020.

Vancouver:

Llerena NEM. Ensembles na classificação relacional. [Internet] [Masters thesis]. University of São Paulo; 2011. [cited 2020 Dec 04]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102011-095113/ ;.

Council of Science Editors:

Llerena NEM. Ensembles na classificação relacional. [Masters Thesis]. University of São Paulo; 2011. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18102011-095113/ ;

18. Chaves, Bruno Butilhão. Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados.

Degree: Mestrado, Engenharia de Controle e Automação Mecânica, 2011, University of São Paulo

O estudo da Inteligência Artificial e de suas técnicas tem trazido grandes resultados para a evolução da tecnologia em diversas áreas. Técnicas já conhecidas como… (more)

Subjects/Keywords: AdaBoost; AdaBoost; Adulteração de combustível; Aprendizagem de máquina; Boosting; Boosting; Dispositivos embarcados; Embedded; Machine learning; Pattern recognition; Reconhecimento de padrão; Sensores

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chaves, B. B. (2011). Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;

Chicago Manual of Style (16th Edition):

Chaves, Bruno Butilhão. “Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados.” 2011. Masters Thesis, University of São Paulo. Accessed December 04, 2020. http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;.

MLA Handbook (7th Edition):

Chaves, Bruno Butilhão. “Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados.” 2011. Web. 04 Dec 2020.

Vancouver:

Chaves BB. Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados. [Internet] [Masters thesis]. University of São Paulo; 2011. [cited 2020 Dec 04]. Available from: http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;.

Council of Science Editors:

Chaves BB. Estudo do algoritmo AdaBoost de aprendizagem de máquina aplicado a sensores e sistemas embarcados. [Masters Thesis]. University of São Paulo; 2011. Available from: http://www.teses.usp.br/teses/disponiveis/3/3152/tde-12062012-163740/ ;


Vilnius University

19. Zareckaitė, Ieva. Veidų segmentacijos algoritmai.

Degree: Master, 2014, Vilnius University

Baigiamajame magistro darbe nagrinėjama automatinės priešakinių veidų segmentacijos skaitmeniniuose vaizduose problematika. Pateikta išsami populiariausių bei su įgyvendinta sistema susijusių veidų segmentacijos metodikų teorinė ir praktinė… (more)

Subjects/Keywords: Veidų segmentacija; Naivusis Bajesas; “boosting” metodika; Klasifikavimas./Face detection; Segmentation; Naï; ve Bayesian; Boosting; Classification

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zareckaitė, Ieva. (2014). Veidų segmentacijos algoritmai. (Masters Thesis). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20140627_165525-66589 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Zareckaitė, Ieva. “Veidų segmentacijos algoritmai.” 2014. Masters Thesis, Vilnius University. Accessed December 04, 2020. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20140627_165525-66589 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Zareckaitė, Ieva. “Veidų segmentacijos algoritmai.” 2014. Web. 04 Dec 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Zareckaitė, Ieva. Veidų segmentacijos algoritmai. [Internet] [Masters thesis]. Vilnius University; 2014. [cited 2020 Dec 04]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20140627_165525-66589 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Zareckaitė, Ieva. Veidų segmentacijos algoritmai. [Masters Thesis]. Vilnius University; 2014. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20140627_165525-66589 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

20. Bahri, Emna. Amélioration des procédures adaptatives pour l'apprentissage supervisé des données réelles : Improving adaptive methods of supervised learning for real data.

Degree: Docteur es, Informatique, 2010, Université Lumière – Lyon II

L'apprentissage automatique doit faire face à différentes difficultés lorsqu'il est confronté aux particularités des données réelles. En effet, ces données sont généralement complexes, volumineuses, de… (more)

Subjects/Keywords: Apprentissage supervisé; Données réelles; Boosting; Bruit; Données déséquilibrées; Classification associative; Supervised Learning; Real data; Boosting; Noise; Imbalanced data; Associative classification

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bahri, E. (2010). Amélioration des procédures adaptatives pour l'apprentissage supervisé des données réelles : Improving adaptive methods of supervised learning for real data. (Doctoral Dissertation). Université Lumière – Lyon II. Retrieved from http://www.theses.fr/2010LYO20089

Chicago Manual of Style (16th Edition):

Bahri, Emna. “Amélioration des procédures adaptatives pour l'apprentissage supervisé des données réelles : Improving adaptive methods of supervised learning for real data.” 2010. Doctoral Dissertation, Université Lumière – Lyon II. Accessed December 04, 2020. http://www.theses.fr/2010LYO20089.

MLA Handbook (7th Edition):

Bahri, Emna. “Amélioration des procédures adaptatives pour l'apprentissage supervisé des données réelles : Improving adaptive methods of supervised learning for real data.” 2010. Web. 04 Dec 2020.

Vancouver:

Bahri E. Amélioration des procédures adaptatives pour l'apprentissage supervisé des données réelles : Improving adaptive methods of supervised learning for real data. [Internet] [Doctoral dissertation]. Université Lumière – Lyon II; 2010. [cited 2020 Dec 04]. Available from: http://www.theses.fr/2010LYO20089.

Council of Science Editors:

Bahri E. Amélioration des procédures adaptatives pour l'apprentissage supervisé des données réelles : Improving adaptive methods of supervised learning for real data. [Doctoral Dissertation]. Université Lumière – Lyon II; 2010. Available from: http://www.theses.fr/2010LYO20089


Brno University of Technology

21. Fér, Radek. Grafické a video příznaky v rozpoznávání mluvčího: Computer Graphics and Video Features for Speaker Recognition.

Degree: 2019, Brno University of Technology

 We describe a non-traditional method for speaker recognition that uses features and algorithms used mainly for computer vision. Important theoretical knowledge of computer recognition is… (more)

Subjects/Keywords: rozpoznávání mluvčího; Boosted Binary Features (BBF); boosting; lokální řečové příznaky; speaker recognition; Boosted Binary Features (BBF); boosting; localized speech features

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fér, R. (2019). Grafické a video příznaky v rozpoznávání mluvčího: Computer Graphics and Video Features for Speaker Recognition. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55281

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Fér, Radek. “Grafické a video příznaky v rozpoznávání mluvčího: Computer Graphics and Video Features for Speaker Recognition.” 2019. Thesis, Brno University of Technology. Accessed December 04, 2020. http://hdl.handle.net/11012/55281.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Fér, Radek. “Grafické a video příznaky v rozpoznávání mluvčího: Computer Graphics and Video Features for Speaker Recognition.” 2019. Web. 04 Dec 2020.

Vancouver:

Fér R. Grafické a video příznaky v rozpoznávání mluvčího: Computer Graphics and Video Features for Speaker Recognition. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/11012/55281.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fér R. Grafické a video příznaky v rozpoznávání mluvčího: Computer Graphics and Video Features for Speaker Recognition. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/55281

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

22. Bourel, Mathias. Agrégation de modèles en apprentissage statistique pour l'estimation de la densité et la classification multiclasse : Aggregate statistical learning methods for density estimation and multiclass problems.

Degree: Docteur es, Mathématiques, 2013, Aix Marseille Université

Les méthodes d'agrégation en apprentissage statistique combinent plusieurs prédicteurs intermédiaires construits à partir du même jeu de données dans le but d'obtenir un prédicteur plus… (more)

Subjects/Keywords: Apprentissage Statistique; Agrégation; Bagging; Boosting; Histogramm; Estimation de la densité; Machine Learning; Agregation; Bagging; Boosting; Histogram; Density estimation; 510

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bourel, M. (2013). Agrégation de modèles en apprentissage statistique pour l'estimation de la densité et la classification multiclasse : Aggregate statistical learning methods for density estimation and multiclass problems. (Doctoral Dissertation). Aix Marseille Université. Retrieved from http://www.theses.fr/2013AIXM4076

Chicago Manual of Style (16th Edition):

Bourel, Mathias. “Agrégation de modèles en apprentissage statistique pour l'estimation de la densité et la classification multiclasse : Aggregate statistical learning methods for density estimation and multiclass problems.” 2013. Doctoral Dissertation, Aix Marseille Université. Accessed December 04, 2020. http://www.theses.fr/2013AIXM4076.

MLA Handbook (7th Edition):

Bourel, Mathias. “Agrégation de modèles en apprentissage statistique pour l'estimation de la densité et la classification multiclasse : Aggregate statistical learning methods for density estimation and multiclass problems.” 2013. Web. 04 Dec 2020.

Vancouver:

Bourel M. Agrégation de modèles en apprentissage statistique pour l'estimation de la densité et la classification multiclasse : Aggregate statistical learning methods for density estimation and multiclass problems. [Internet] [Doctoral dissertation]. Aix Marseille Université 2013. [cited 2020 Dec 04]. Available from: http://www.theses.fr/2013AIXM4076.

Council of Science Editors:

Bourel M. Agrégation de modèles en apprentissage statistique pour l'estimation de la densité et la classification multiclasse : Aggregate statistical learning methods for density estimation and multiclass problems. [Doctoral Dissertation]. Aix Marseille Université 2013. Available from: http://www.theses.fr/2013AIXM4076

23. Foucard, Rémi. Fusion multi-niveaux par boosting pour le tagging automatique : Multi-level fusion by boosting for automatic tagging.

Degree: Docteur es, Signal et images, 2013, Paris, ENST

Les tags constituent un outil très utile pour indexer des documents multimédias. Cette thèse de doctorat s’intéresse au tagging automatique, c’est à dire l’association automatique… (more)

Subjects/Keywords: Extraction de l'information musicale; Fusion de classifieurs; Taggage automatique; Boosting; Music information retrieval; Classifiers fusion; Automatic tagging; Boosting

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Foucard, R. (2013). Fusion multi-niveaux par boosting pour le tagging automatique : Multi-level fusion by boosting for automatic tagging. (Doctoral Dissertation). Paris, ENST. Retrieved from http://www.theses.fr/2013ENST0093

Chicago Manual of Style (16th Edition):

Foucard, Rémi. “Fusion multi-niveaux par boosting pour le tagging automatique : Multi-level fusion by boosting for automatic tagging.” 2013. Doctoral Dissertation, Paris, ENST. Accessed December 04, 2020. http://www.theses.fr/2013ENST0093.

MLA Handbook (7th Edition):

Foucard, Rémi. “Fusion multi-niveaux par boosting pour le tagging automatique : Multi-level fusion by boosting for automatic tagging.” 2013. Web. 04 Dec 2020.

Vancouver:

Foucard R. Fusion multi-niveaux par boosting pour le tagging automatique : Multi-level fusion by boosting for automatic tagging. [Internet] [Doctoral dissertation]. Paris, ENST; 2013. [cited 2020 Dec 04]. Available from: http://www.theses.fr/2013ENST0093.

Council of Science Editors:

Foucard R. Fusion multi-niveaux par boosting pour le tagging automatique : Multi-level fusion by boosting for automatic tagging. [Doctoral Dissertation]. Paris, ENST; 2013. Available from: http://www.theses.fr/2013ENST0093


Brno University of Technology

24. Mrnuštík, Michal. Boosting a evoluční algoritmy: Boosting and Evolution.

Degree: 2018, Brno University of Technology

 This thesis introduces combination of the AdaBoost and the evolutionary algorithm. The evolutionary algorithm is used to find linear combination of Haar features. This linear… (more)

Subjects/Keywords: boosting; adaboost; evoluční algoritmy; rozpoznávání vzorů; haarovy příznaky; boosting; adaboost; evolutionary algorithms; pattern recognition; haar features

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mrnuštík, M. (2018). Boosting a evoluční algoritmy: Boosting and Evolution. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55453

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2018. Thesis, Brno University of Technology. Accessed December 04, 2020. http://hdl.handle.net/11012/55453.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2018. Web. 04 Dec 2020.

Vancouver:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/11012/55453.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/55453

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brno University of Technology

25. Mrnuštík, Michal. Boosting a evoluční algoritmy: Boosting and Evolution.

Degree: 2020, Brno University of Technology

 This thesis introduces combination of the AdaBoost and the evolutionary algorithm. The evolutionary algorithm is used to find linear combination of Haar features. This linear… (more)

Subjects/Keywords: boosting; adaboost; evoluční algoritmy; rozpoznávání vzorů; haarovy příznaky; boosting; adaboost; evolutionary algorithms; pattern recognition; haar features

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mrnuštík, M. (2020). Boosting a evoluční algoritmy: Boosting and Evolution. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/188193

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2020. Thesis, Brno University of Technology. Accessed December 04, 2020. http://hdl.handle.net/11012/188193.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mrnuštík, Michal. “Boosting a evoluční algoritmy: Boosting and Evolution.” 2020. Web. 04 Dec 2020.

Vancouver:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/11012/188193.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mrnuštík M. Boosting a evoluční algoritmy: Boosting and Evolution. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/188193

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

26. Wang, Bo. ADAPATIVE BOOSTING IN NONLOCAL IMAGE DENOISING ALGORITHMS.

Degree: PhD, Electrical Engineering, 2017, Texas A&M University

 In the past decade, much progress has been made in image denoising due to the use of low-rank representation and sparse coding, the performance of… (more)

Subjects/Keywords: image denoising; adpative boosting

…many denoising schemes (e.g., [8, 9]) have an iterative boosting step… …x5B;22, 23]. Boosting is motivated by the iterative nature of nonlinear inverse… …information due to imperfect denoising. Another recent work on boosting [26] strengthens… …boosting schemes [8, 9] feed back a fixed portion of the residual noise (the… …residual noise decreases from one iteration to another in the boosting process. Ideally the… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, B. (2017). ADAPATIVE BOOSTING IN NONLOCAL IMAGE DENOISING ALGORITHMS. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/169609

Chicago Manual of Style (16th Edition):

Wang, Bo. “ADAPATIVE BOOSTING IN NONLOCAL IMAGE DENOISING ALGORITHMS.” 2017. Doctoral Dissertation, Texas A&M University. Accessed December 04, 2020. http://hdl.handle.net/1969.1/169609.

MLA Handbook (7th Edition):

Wang, Bo. “ADAPATIVE BOOSTING IN NONLOCAL IMAGE DENOISING ALGORITHMS.” 2017. Web. 04 Dec 2020.

Vancouver:

Wang B. ADAPATIVE BOOSTING IN NONLOCAL IMAGE DENOISING ALGORITHMS. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1969.1/169609.

Council of Science Editors:

Wang B. ADAPATIVE BOOSTING IN NONLOCAL IMAGE DENOISING ALGORITHMS. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/169609


Vilnius University

27. Verbel, Irina. Neuroninių tinklų architektūros parinkimas.

Degree: Master, 2009, Vilnius University

Darbe aprašytas modelis, naudojant aktyvacijos funkcijas su Gauso branduoliais. Vienu atveju buvo paimtos aktyvacijos funkcijos, maksimizuojančios Shannon entropija, kitu – maksimizuojančios Renyi entropiją. Manoma, kad… (more)

Subjects/Keywords: Neuroniniai tuinklai; Kernel-Gauso modelis; "boosting search" metodas

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Verbel, Irina. (2009). Neuroninių tinklų architektūros parinkimas. (Masters Thesis). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184401-63341 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Verbel, Irina. “Neuroninių tinklų architektūros parinkimas.” 2009. Masters Thesis, Vilnius University. Accessed December 04, 2020. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184401-63341 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Verbel, Irina. “Neuroninių tinklų architektūros parinkimas.” 2009. Web. 04 Dec 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Verbel, Irina. Neuroninių tinklų architektūros parinkimas. [Internet] [Masters thesis]. Vilnius University; 2009. [cited 2020 Dec 04]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184401-63341 ;.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Verbel, Irina. Neuroninių tinklų architektūros parinkimas. [Masters Thesis]. Vilnius University; 2009. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2006~D_20081203_184401-63341 ;

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Pontifical Catholic University of Rio de Janeiro

28. JULIO CESAR DUARTE. [en] THE BOOSTING AT START ALGORITHM AND ITS APPLICATIONS.

Degree: 2017, Pontifical Catholic University of Rio de Janeiro

[pt] Boosting é uma técnica de aprendizado de máquina que combina diversos classificadores fracos com o objetivo de melhorar a acurácia geral. Em cada iteração,… (more)

Subjects/Keywords: [pt] APRENDIZADO DE MAQUINA; [en] MACHINE LEARNING; [pt] BOOSTING; [en] BOOSTING; [pt] PROCESSAMENTO DE LINGUAGEM NATURAL; [en] NATURAL LANGUAGE PROCESSING; [pt] ALGORITMOS DE COMITE; [en] ENSEMBLE ALGORITHMS; [pt] ADABOOST; [en] ADABOOST; [pt] BOOSTING AT START; [en] BOOSTING AT START

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

DUARTE, J. C. (2017). [en] THE BOOSTING AT START ALGORITHM AND ITS APPLICATIONS. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31451

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

DUARTE, JULIO CESAR. “[en] THE BOOSTING AT START ALGORITHM AND ITS APPLICATIONS.” 2017. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed December 04, 2020. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31451.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

DUARTE, JULIO CESAR. “[en] THE BOOSTING AT START ALGORITHM AND ITS APPLICATIONS.” 2017. Web. 04 Dec 2020.

Vancouver:

DUARTE JC. [en] THE BOOSTING AT START ALGORITHM AND ITS APPLICATIONS. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2017. [cited 2020 Dec 04]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31451.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

DUARTE JC. [en] THE BOOSTING AT START ALGORITHM AND ITS APPLICATIONS. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2017. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31451

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. Faddoul, Jean-Baptiste. Méthodes d’ensembles pour l’apprentissage multi-tâche avec des tâches hétérogènes et sans restrictions : Ensemble Methods to Learn Multiple Heterogenous Tasks without Restrictions.

Degree: Docteur es, Informatique, 2012, Lille 3

Apprendre des tâches simultanément peut améliorer la performance de prédiction par rapport à l'apprentissage de ces tâches de manière indépendante. Dans cette thèse, nous considérons… (more)

Subjects/Keywords: Apprentissage automatique; Boosting (algorithmes); Fonctionnement multitâche; Machine Learning; Multi-Task Learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Faddoul, J. (2012). Méthodes d’ensembles pour l’apprentissage multi-tâche avec des tâches hétérogènes et sans restrictions : Ensemble Methods to Learn Multiple Heterogenous Tasks without Restrictions. (Doctoral Dissertation). Lille 3. Retrieved from http://www.theses.fr/2012LIL30059

Chicago Manual of Style (16th Edition):

Faddoul, Jean-Baptiste. “Méthodes d’ensembles pour l’apprentissage multi-tâche avec des tâches hétérogènes et sans restrictions : Ensemble Methods to Learn Multiple Heterogenous Tasks without Restrictions.” 2012. Doctoral Dissertation, Lille 3. Accessed December 04, 2020. http://www.theses.fr/2012LIL30059.

MLA Handbook (7th Edition):

Faddoul, Jean-Baptiste. “Méthodes d’ensembles pour l’apprentissage multi-tâche avec des tâches hétérogènes et sans restrictions : Ensemble Methods to Learn Multiple Heterogenous Tasks without Restrictions.” 2012. Web. 04 Dec 2020.

Vancouver:

Faddoul J. Méthodes d’ensembles pour l’apprentissage multi-tâche avec des tâches hétérogènes et sans restrictions : Ensemble Methods to Learn Multiple Heterogenous Tasks without Restrictions. [Internet] [Doctoral dissertation]. Lille 3; 2012. [cited 2020 Dec 04]. Available from: http://www.theses.fr/2012LIL30059.

Council of Science Editors:

Faddoul J. Méthodes d’ensembles pour l’apprentissage multi-tâche avec des tâches hétérogènes et sans restrictions : Ensemble Methods to Learn Multiple Heterogenous Tasks without Restrictions. [Doctoral Dissertation]. Lille 3; 2012. Available from: http://www.theses.fr/2012LIL30059


University of Toronto

30. Pyda, Susanne. Feature Engineering and Machine Learning Methodologies using Customer Debit and Credit Transactions for Predicting Savings Account and Home Equity Line of Credit Acquisition.

Degree: 2019, University of Toronto

The objective of this thesis is to investigate feature engineering methodologies for customer credit and debit transaction data and evaluate their utility in developing machine… (more)

Subjects/Keywords: feature engineering; financial services; gradient boosting; machine learning; xgboost; 0489

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pyda, S. (2019). Feature Engineering and Machine Learning Methodologies using Customer Debit and Credit Transactions for Predicting Savings Account and Home Equity Line of Credit Acquisition. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/98287

Chicago Manual of Style (16th Edition):

Pyda, Susanne. “Feature Engineering and Machine Learning Methodologies using Customer Debit and Credit Transactions for Predicting Savings Account and Home Equity Line of Credit Acquisition.” 2019. Masters Thesis, University of Toronto. Accessed December 04, 2020. http://hdl.handle.net/1807/98287.

MLA Handbook (7th Edition):

Pyda, Susanne. “Feature Engineering and Machine Learning Methodologies using Customer Debit and Credit Transactions for Predicting Savings Account and Home Equity Line of Credit Acquisition.” 2019. Web. 04 Dec 2020.

Vancouver:

Pyda S. Feature Engineering and Machine Learning Methodologies using Customer Debit and Credit Transactions for Predicting Savings Account and Home Equity Line of Credit Acquisition. [Internet] [Masters thesis]. University of Toronto; 2019. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1807/98287.

Council of Science Editors:

Pyda S. Feature Engineering and Machine Learning Methodologies using Customer Debit and Credit Transactions for Predicting Savings Account and Home Equity Line of Credit Acquisition. [Masters Thesis]. University of Toronto; 2019. Available from: http://hdl.handle.net/1807/98287

[1] [2] [3] [4] [5] [6] [7] [8]

.