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 +publisher:"Delft University of Technology" +contributor:("Loog, Marco"). Showing records 1 – 19 of 19 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Delft University of Technology

1. Raats, Jason (author). Using cost-sensitive learning to forecast football matches.

Degree: 2018, Delft University of Technology

Forecasting football match outcomes have been investigated previously, with the primary goal of these studies being to accurately predict the outcome for the highest number… (more)

Subjects/Keywords: machine learning; sports betting; cost-sensitive learning; decision trees

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Raats, J. (. (2018). Using cost-sensitive learning to forecast football matches. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:8d477094-a6ce-4be8-acf4-3b21f195b6c4

Chicago Manual of Style (16th Edition):

Raats, Jason (author). “Using cost-sensitive learning to forecast football matches.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:8d477094-a6ce-4be8-acf4-3b21f195b6c4.

MLA Handbook (7th Edition):

Raats, Jason (author). “Using cost-sensitive learning to forecast football matches.” 2018. Web. 30 Nov 2020.

Vancouver:

Raats J(. Using cost-sensitive learning to forecast football matches. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:8d477094-a6ce-4be8-acf4-3b21f195b6c4.

Council of Science Editors:

Raats J(. Using cost-sensitive learning to forecast football matches. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:8d477094-a6ce-4be8-acf4-3b21f195b6c4


Delft University of Technology

2. Bertazzi, Andrea (author). Safe Semi-Supervised Learning.

Degree: 2018, Delft University of Technology

Semi-supervised algorithms have been shown to possibly have a worse performance than the corresponding supervised model. This may be due to a violation of the… (more)

Subjects/Keywords: semi-supervised learning; contrast; pessimism; parameter estimation; monotone sample; maximum likelihood estimation

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Bertazzi, A. (. (2018). Safe Semi-Supervised Learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5784060f-b67c-406c-ba30-20d456e503af

Chicago Manual of Style (16th Edition):

Bertazzi, Andrea (author). “Safe Semi-Supervised Learning.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:5784060f-b67c-406c-ba30-20d456e503af.

MLA Handbook (7th Edition):

Bertazzi, Andrea (author). “Safe Semi-Supervised Learning.” 2018. Web. 30 Nov 2020.

Vancouver:

Bertazzi A(. Safe Semi-Supervised Learning. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:5784060f-b67c-406c-ba30-20d456e503af.

Council of Science Editors:

Bertazzi A(. Safe Semi-Supervised Learning. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:5784060f-b67c-406c-ba30-20d456e503af


Delft University of Technology

3. Juchli, Marc (author). Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data.

Degree: 2018, Delft University of Technology

 For various reasons, financial institutions often make use of high-level trading strategies when buying and selling assets. Many individuals, irrespective or their level of prior… (more)

Subjects/Keywords: Reinforcement Learning; Q-Learning; Deep Q-Network; deep reinforcement learning; limit order; limit order placement; trading

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Juchli, M. (. (2018). Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a

Chicago Manual of Style (16th Edition):

Juchli, Marc (author). “Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a.

MLA Handbook (7th Edition):

Juchli, Marc (author). “Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data.” 2018. Web. 30 Nov 2020.

Vancouver:

Juchli M(. Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a.

Council of Science Editors:

Juchli M(. Limit order placement optimization with Deep Reinforcement Learning: Learning from patterns in cryptocurrency market data. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:e2e99579-541b-4b5a-8cbb-36ea17a4a93a


Delft University of Technology

4. Vos, Daniël (author). Adversarially Robust Decision Trees Against User-Specified Threat Models.

Degree: 2020, Delft University of Technology

In the present day we use machine learning for sensitive tasks that require models to be both understandable and robust. Although traditional models such as… (more)

Subjects/Keywords: Adversarial Machine Learning; Decision Trees; Cyber Security

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Vos, D. (. (2020). Adversarially Robust Decision Trees Against User-Specified Threat Models. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:c9d9cdc6-4f98-4730-8fb6-43e6e3444002

Chicago Manual of Style (16th Edition):

Vos, Daniël (author). “Adversarially Robust Decision Trees Against User-Specified Threat Models.” 2020. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:c9d9cdc6-4f98-4730-8fb6-43e6e3444002.

MLA Handbook (7th Edition):

Vos, Daniël (author). “Adversarially Robust Decision Trees Against User-Specified Threat Models.” 2020. Web. 30 Nov 2020.

Vancouver:

Vos D(. Adversarially Robust Decision Trees Against User-Specified Threat Models. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:c9d9cdc6-4f98-4730-8fb6-43e6e3444002.

Council of Science Editors:

Vos D(. Adversarially Robust Decision Trees Against User-Specified Threat Models. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:c9d9cdc6-4f98-4730-8fb6-43e6e3444002


Delft University of Technology

5. Anand, Kanav (author). Black Magic in Deep Learning: Understanding the role of humans in hyperparameter optimization.

Degree: 2019, Delft University of Technology

Deep learning is proving to be a useful tool in solving problems from various domains. Despite a rich research activity leading to numerous interesting deep… (more)

Subjects/Keywords: hyperparameter optimization; deep learning; machine learning; user study

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Anand, K. (. (2019). Black Magic in Deep Learning: Understanding the role of humans in hyperparameter optimization. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7a9df9fb-5dc4-4d72-a966-45edbb2bc942

Chicago Manual of Style (16th Edition):

Anand, Kanav (author). “Black Magic in Deep Learning: Understanding the role of humans in hyperparameter optimization.” 2019. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:7a9df9fb-5dc4-4d72-a966-45edbb2bc942.

MLA Handbook (7th Edition):

Anand, Kanav (author). “Black Magic in Deep Learning: Understanding the role of humans in hyperparameter optimization.” 2019. Web. 30 Nov 2020.

Vancouver:

Anand K(. Black Magic in Deep Learning: Understanding the role of humans in hyperparameter optimization. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:7a9df9fb-5dc4-4d72-a966-45edbb2bc942.

Council of Science Editors:

Anand K(. Black Magic in Deep Learning: Understanding the role of humans in hyperparameter optimization. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:7a9df9fb-5dc4-4d72-a966-45edbb2bc942


Delft University of Technology

6. Jurasiński, Karol (author). Towards deeper understanding of semi-supervised learning with variational autoencoders.

Degree: 2019, Delft University of Technology

 Recently, deep generative models have been shown to achieve state-of-the-art performance on semi-supervised learning tasks. In particular, variational autoencoders have been adopted to use labeled… (more)

Subjects/Keywords: semi-supervised learning; variational inference; deep learning; machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Jurasiński, K. (. (2019). Towards deeper understanding of semi-supervised learning with variational autoencoders. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb

Chicago Manual of Style (16th Edition):

Jurasiński, Karol (author). “Towards deeper understanding of semi-supervised learning with variational autoencoders.” 2019. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb.

MLA Handbook (7th Edition):

Jurasiński, Karol (author). “Towards deeper understanding of semi-supervised learning with variational autoencoders.” 2019. Web. 30 Nov 2020.

Vancouver:

Jurasiński K(. Towards deeper understanding of semi-supervised learning with variational autoencoders. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb.

Council of Science Editors:

Jurasiński K(. Towards deeper understanding of semi-supervised learning with variational autoencoders. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:e92c56a8-72a6-48d2-9205-a78cbc889ffb


Delft University of Technology

7. Garbacz, Mateusz (author). Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction.

Degree: 2018, Delft University of Technology

 Being capable to foresee the future of a given financial asset as an investor, may lead to significant economic profits. Therefore, stock market prediction is… (more)

Subjects/Keywords: Bitcoin; Bubble; Prediction; Machine Learning; Deep Learning; Non-stationarity

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Garbacz, M. (. (2018). Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0

Chicago Manual of Style (16th Edition):

Garbacz, Mateusz (author). “Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0.

MLA Handbook (7th Edition):

Garbacz, Mateusz (author). “Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction.” 2018. Web. 30 Nov 2020.

Vancouver:

Garbacz M(. Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0.

Council of Science Editors:

Garbacz M(. Time series forecast in non-stationary environment with occurrence of economic bubbles: Bitcoin Price prediction. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:13d6eb0e-4b34-4a41-86a8-9cbab66ecfa0


Delft University of Technology

8. Radojević, Jovana (author). Cooperative Visual Object Learning.

Degree: 2017, Delft University of Technology

 A lot of attention has recently been focused on possible benefits of the cooperation between machines and humans. Taking the best from machines and humans… (more)

Subjects/Keywords: selv-evaluation of classifiers; object recognition; Object learning; Visual System; cooperative object learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Radojević, J. (. (2017). Cooperative Visual Object Learning. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:90383567-fc0d-4775-bb52-613b7074a676

Chicago Manual of Style (16th Edition):

Radojević, Jovana (author). “Cooperative Visual Object Learning.” 2017. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:90383567-fc0d-4775-bb52-613b7074a676.

MLA Handbook (7th Edition):

Radojević, Jovana (author). “Cooperative Visual Object Learning.” 2017. Web. 30 Nov 2020.

Vancouver:

Radojević J(. Cooperative Visual Object Learning. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:90383567-fc0d-4775-bb52-613b7074a676.

Council of Science Editors:

Radojević J(. Cooperative Visual Object Learning. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:90383567-fc0d-4775-bb52-613b7074a676


Delft University of Technology

9. van Bekkum, Rob (author). Learning and Optimizing Probabilistic Models for Planning under Uncertainty.

Degree: 2017, Delft University of Technology

Decision-theoretic planning techniques are increasingly being used to obtain (optimal) plans for domains involving uncertainty, which may be present in the form of the controlling… (more)

Subjects/Keywords: planning under uncertainty; Bayesian Optimization; probabilistic model learning; Markov Decision Processes; decision-theoretic planning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Bekkum, R. (. (2017). Learning and Optimizing Probabilistic Models for Planning under Uncertainty. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:37e80be9-ab78-427b-b317-c5529a752d7d

Chicago Manual of Style (16th Edition):

van Bekkum, Rob (author). “Learning and Optimizing Probabilistic Models for Planning under Uncertainty.” 2017. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:37e80be9-ab78-427b-b317-c5529a752d7d.

MLA Handbook (7th Edition):

van Bekkum, Rob (author). “Learning and Optimizing Probabilistic Models for Planning under Uncertainty.” 2017. Web. 30 Nov 2020.

Vancouver:

van Bekkum R(. Learning and Optimizing Probabilistic Models for Planning under Uncertainty. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:37e80be9-ab78-427b-b317-c5529a752d7d.

Council of Science Editors:

van Bekkum R(. Learning and Optimizing Probabilistic Models for Planning under Uncertainty. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:37e80be9-ab78-427b-b317-c5529a752d7d


Delft University of Technology

10. Wen, Xiaoming (author). Learning Scale-Aware Optical Flow.

Degree: 2018, Delft University of Technology

 Optical flow is a representation of projected real-world motion of the object between two consecutive images. The optical flow measures the pixel displacement on the… (more)

Subjects/Keywords: Optica Flow; CNN; Scale-Aware; Derivative

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Wen, X. (. (2018). Learning Scale-Aware Optical Flow. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c

Chicago Manual of Style (16th Edition):

Wen, Xiaoming (author). “Learning Scale-Aware Optical Flow.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c.

MLA Handbook (7th Edition):

Wen, Xiaoming (author). “Learning Scale-Aware Optical Flow.” 2018. Web. 30 Nov 2020.

Vancouver:

Wen X(. Learning Scale-Aware Optical Flow. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c.

Council of Science Editors:

Wen X(. Learning Scale-Aware Optical Flow. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:7e29ed6a-b1d8-490b-bfa0-b576e6e7887c


Delft University of Technology

11. Naseri Jahfari, Arman (author). Domain Adaptation in Acoustic Rainfall Sensors.

Degree: 2019, Delft University of Technology

 Rainfall is increasing in frequency and intensity due to climate change. Hydrological models exist that can report bottlenecks in urban infrastructures. However, these require accurate… (more)

Subjects/Keywords: Domain Adaptation; Pattern Recognition; Rainfall estimation; Acoustic Sensor

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Naseri Jahfari, A. (. (2019). Domain Adaptation in Acoustic Rainfall Sensors. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a4b79bdf-e15d-49c7-ac50-3cfe0dbe5940

Chicago Manual of Style (16th Edition):

Naseri Jahfari, Arman (author). “Domain Adaptation in Acoustic Rainfall Sensors.” 2019. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:a4b79bdf-e15d-49c7-ac50-3cfe0dbe5940.

MLA Handbook (7th Edition):

Naseri Jahfari, Arman (author). “Domain Adaptation in Acoustic Rainfall Sensors.” 2019. Web. 30 Nov 2020.

Vancouver:

Naseri Jahfari A(. Domain Adaptation in Acoustic Rainfall Sensors. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:a4b79bdf-e15d-49c7-ac50-3cfe0dbe5940.

Council of Science Editors:

Naseri Jahfari A(. Domain Adaptation in Acoustic Rainfall Sensors. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:a4b79bdf-e15d-49c7-ac50-3cfe0dbe5940


Delft University of Technology

12. Starre, Rolf (author). Action Selection Policies for Walking Monte Carlo Tree Search.

Degree: 2018, Delft University of Technology

 Recent Reinforcement Learning methods have combined function approximation and Monte Carlo Tree Search and are able to learn by self-play up to a very high… (more)

Subjects/Keywords: Monte Carlo Tree Search; Reinforcement Learning; Exploration; Action selection policies

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Starre, R. (. (2018). Action Selection Policies for Walking Monte Carlo Tree Search. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9

Chicago Manual of Style (16th Edition):

Starre, Rolf (author). “Action Selection Policies for Walking Monte Carlo Tree Search.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9.

MLA Handbook (7th Edition):

Starre, Rolf (author). “Action Selection Policies for Walking Monte Carlo Tree Search.” 2018. Web. 30 Nov 2020.

Vancouver:

Starre R(. Action Selection Policies for Walking Monte Carlo Tree Search. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9.

Council of Science Editors:

Starre R(. Action Selection Policies for Walking Monte Carlo Tree Search. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:3947ef53-eab3-46a2-9efc-fff985cd96c9


Delft University of Technology

13. Razoux Schultz, Lex (author). Distance Based Source Domain Selection for Automated Sentiment Classification.

Degree: 2018, Delft University of Technology

Automated Sentiment Classification (SC) on short text fragments has been an upcoming field of research. Different machine learning techniques and word representation models have proven… (more)

Subjects/Keywords: sentiment analysis; sentiment classification; domain adaptation; source selection; domain selection

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Razoux Schultz, L. (. (2018). Distance Based Source Domain Selection for Automated Sentiment Classification. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196

Chicago Manual of Style (16th Edition):

Razoux Schultz, Lex (author). “Distance Based Source Domain Selection for Automated Sentiment Classification.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196.

MLA Handbook (7th Edition):

Razoux Schultz, Lex (author). “Distance Based Source Domain Selection for Automated Sentiment Classification.” 2018. Web. 30 Nov 2020.

Vancouver:

Razoux Schultz L(. Distance Based Source Domain Selection for Automated Sentiment Classification. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196.

Council of Science Editors:

Razoux Schultz L(. Distance Based Source Domain Selection for Automated Sentiment Classification. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196


Delft University of Technology

14. Ju, Jihong (author). Learn representations in the presence of segmentation label noises.

Degree: 2017, Delft University of Technology

 Training data for segmentation tasks are often available only on a small scale. Transferring learned representations from pre-trained classification models is therefore widely adopted by… (more)

Subjects/Keywords: Transfer learning; Image segmentation; PU learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Ju, J. (. (2017). Learn representations in the presence of segmentation label noises. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:202633b6-4fb1-463a-a29e-b2f3e2402c00

Chicago Manual of Style (16th Edition):

Ju, Jihong (author). “Learn representations in the presence of segmentation label noises.” 2017. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:202633b6-4fb1-463a-a29e-b2f3e2402c00.

MLA Handbook (7th Edition):

Ju, Jihong (author). “Learn representations in the presence of segmentation label noises.” 2017. Web. 30 Nov 2020.

Vancouver:

Ju J(. Learn representations in the presence of segmentation label noises. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:202633b6-4fb1-463a-a29e-b2f3e2402c00.

Council of Science Editors:

Ju J(. Learn representations in the presence of segmentation label noises. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:202633b6-4fb1-463a-a29e-b2f3e2402c00


Delft University of Technology

15. Strafforello, Ombretta (author). Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches.

Degree: 2019, Delft University of Technology

 With the huge amount of data that is collected every day and shared on the internet, many recent studies have focused on methods to make… (more)

Subjects/Keywords: Machine Learning; Multimodal Machine Learning; Video analysis; Highlights extraction; Crowdsourcing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Strafforello, O. (. (2019). Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:a6f1d8c3-9915-4a31-aca7-953965f4454e

Chicago Manual of Style (16th Edition):

Strafforello, Ombretta (author). “Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches.” 2019. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:a6f1d8c3-9915-4a31-aca7-953965f4454e.

MLA Handbook (7th Edition):

Strafforello, Ombretta (author). “Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches.” 2019. Web. 30 Nov 2020.

Vancouver:

Strafforello O(. Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:a6f1d8c3-9915-4a31-aca7-953965f4454e.

Council of Science Editors:

Strafforello O(. Multimodal information extraction from videos: Automatic creation of highlight clips from political speeches. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:a6f1d8c3-9915-4a31-aca7-953965f4454e


Delft University of Technology

16. van Bekhoven, Sjoerd (author). Predicting voluntary employee turnover using core employee data.

Degree: 2017, Delft University of Technology

 Voluntary employee turnover is the process of an employee voluntarily choosing to resign from a company. High voluntary turnover has been shown to have negative… (more)

Subjects/Keywords: voluntary employee turnover; people analytics; binary classification; feature design; class imbalance; class overlap; feature importance

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Bekhoven, S. (. (2017). Predicting voluntary employee turnover using core employee data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0

Chicago Manual of Style (16th Edition):

van Bekhoven, Sjoerd (author). “Predicting voluntary employee turnover using core employee data.” 2017. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0.

MLA Handbook (7th Edition):

van Bekhoven, Sjoerd (author). “Predicting voluntary employee turnover using core employee data.” 2017. Web. 30 Nov 2020.

Vancouver:

van Bekhoven S(. Predicting voluntary employee turnover using core employee data. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0.

Council of Science Editors:

van Bekhoven S(. Predicting voluntary employee turnover using core employee data. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:95411815-890a-4aba-b6e0-336c9080cfc0


Delft University of Technology

17. Gabriel, Luka (author). MRI-based virtual CT generation from unpaired data.

Degree: 2018, Delft University of Technology

Both MRI and CT imaging are commonly used and combined in medical imaging because of their complementary information about soft tissue and bone respectively. However,… (more)

Subjects/Keywords: Medical Imaging; MRI; CT; Deep Learning; CycleGAN

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Gabriel, L. (. (2018). MRI-based virtual CT generation from unpaired data. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9be59b26-996c-4c0b-903d-00caffb5d018

Chicago Manual of Style (16th Edition):

Gabriel, Luka (author). “MRI-based virtual CT generation from unpaired data.” 2018. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:9be59b26-996c-4c0b-903d-00caffb5d018.

MLA Handbook (7th Edition):

Gabriel, Luka (author). “MRI-based virtual CT generation from unpaired data.” 2018. Web. 30 Nov 2020.

Vancouver:

Gabriel L(. MRI-based virtual CT generation from unpaired data. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:9be59b26-996c-4c0b-903d-00caffb5d018.

Council of Science Editors:

Gabriel L(. MRI-based virtual CT generation from unpaired data. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:9be59b26-996c-4c0b-903d-00caffb5d018


Delft University of Technology

18. Zhou, Yuan (author). Generating virtual CT from MRI using fully convolutional neural networks with improved structure quality.

Degree: 2017, Delft University of Technology

Computer Science

EIT Digital

Digital Media Technology

Advisors/Committee Members: Loog, Marco (mentor), Delft University of Technology (degree granting institution).

Subjects/Keywords: virtual CT; Fully Convolutional Neural network; Loss Functions; Image Quality Assessment; Structure Similarity

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Zhou, Y. (. (2017). Generating virtual CT from MRI using fully convolutional neural networks with improved structure quality. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:962cb020-4b9b-4ce5-afa2-95775bcf5761

Chicago Manual of Style (16th Edition):

Zhou, Yuan (author). “Generating virtual CT from MRI using fully convolutional neural networks with improved structure quality.” 2017. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:962cb020-4b9b-4ce5-afa2-95775bcf5761.

MLA Handbook (7th Edition):

Zhou, Yuan (author). “Generating virtual CT from MRI using fully convolutional neural networks with improved structure quality.” 2017. Web. 30 Nov 2020.

Vancouver:

Zhou Y(. Generating virtual CT from MRI using fully convolutional neural networks with improved structure quality. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:962cb020-4b9b-4ce5-afa2-95775bcf5761.

Council of Science Editors:

Zhou Y(. Generating virtual CT from MRI using fully convolutional neural networks with improved structure quality. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:962cb020-4b9b-4ce5-afa2-95775bcf5761


Delft University of Technology

19. van Dorth, Matthijs (author). Probabilistic Models for Personalized Faceted Search.

Degree: 2017, Delft University of Technology

Pattern Recognition & Bioinformatics Advisors/Committee Members: Reinders, Marcel (mentor), Loog, Marco (mentor), Liem, Cynthia (mentor), Kooij, Julian (mentor), Delft University of Technology (degree granting institution).

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

van Dorth, M. (. (2017). Probabilistic Models for Personalized Faceted Search. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481

Chicago Manual of Style (16th Edition):

van Dorth, Matthijs (author). “Probabilistic Models for Personalized Faceted Search.” 2017. Masters Thesis, Delft University of Technology. Accessed November 30, 2020. http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481.

MLA Handbook (7th Edition):

van Dorth, Matthijs (author). “Probabilistic Models for Personalized Faceted Search.” 2017. Web. 30 Nov 2020.

Vancouver:

van Dorth M(. Probabilistic Models for Personalized Faceted Search. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Nov 30]. Available from: http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481.

Council of Science Editors:

van Dorth M(. Probabilistic Models for Personalized Faceted Search. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:71486f25-5e91-4968-9a37-14907fee6481

.