Advanced search options

Sorted by: relevance · author · university · date | New search

You searched for `+publisher:"Georgia Tech" +contributor:("Balcan, Maria-Florina")`

.
Showing records 1 – 16 of
16 total matches.

▼ Search Limiters

1. Balasubramanian, Krishnakumar. Learning matrix and functional models in high-dimensions.

Degree: PhD, Computer Science, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/52284

► Statistical machine learning methods provide us with a principled framework for extracting meaningful information from noisy high-dimensional data sets. A significant feature of such procedures…
(more)

Subjects/Keywords: Statistics; Machine learning; Matrix; Kernel; Consistency

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Balasubramanian, K. (2014). Learning matrix and functional models in high-dimensions. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52284

Chicago Manual of Style (16^{th} Edition):

Balasubramanian, Krishnakumar. “Learning matrix and functional models in high-dimensions.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/52284.

MLA Handbook (7^{th} Edition):

Balasubramanian, Krishnakumar. “Learning matrix and functional models in high-dimensions.” 2014. Web. 18 Apr 2021.

Vancouver:

Balasubramanian K. Learning matrix and functional models in high-dimensions. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/52284.

Council of Science Editors:

Balasubramanian K. Learning matrix and functional models in high-dimensions. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52284

2. Ganti Mahapatruni, Ravi Sastry. New formulations for active learning.

Degree: PhD, Computer Science, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/51801

► In this thesis, we provide computationally efficient algorithms with provable statistical guarantees, for the problem of active learning, by using ideas from sequential analysis. We…
(more)

Subjects/Keywords: Active learning; Sequential analysis; Stochastic optimization; Active learning; Algorithms; Sequential analysis; Mathematical optimization; Machine learning

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Ganti Mahapatruni, R. S. (2014). New formulations for active learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51801

Chicago Manual of Style (16^{th} Edition):

Ganti Mahapatruni, Ravi Sastry. “New formulations for active learning.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/51801.

MLA Handbook (7^{th} Edition):

Ganti Mahapatruni, Ravi Sastry. “New formulations for active learning.” 2014. Web. 18 Apr 2021.

Vancouver:

Ganti Mahapatruni RS. New formulations for active learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/51801.

Council of Science Editors:

Ganti Mahapatruni RS. New formulations for active learning. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/51801

3. He, Niao. Saddle point techniques in convex composite and error-in-measurement optimization.

Degree: PhD, Industrial and Systems Engineering, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/54400

► This dissertation aims to develop efficient algorithms with improved scalability and stability properties for large-scale optimization and optimization under uncertainty, and to bridge some of…
(more)

Subjects/Keywords: Nonsmooth optimization; Composite minimization; First order methods; Stochastic optimization; Mirror prox

Record Details Similar Records

❌

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

APA (6^{th} Edition):

He, N. (2015). Saddle point techniques in convex composite and error-in-measurement optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54400

Chicago Manual of Style (16^{th} Edition):

He, Niao. “Saddle point techniques in convex composite and error-in-measurement optimization.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/54400.

MLA Handbook (7^{th} Edition):

He, Niao. “Saddle point techniques in convex composite and error-in-measurement optimization.” 2015. Web. 18 Apr 2021.

Vancouver:

He N. Saddle point techniques in convex composite and error-in-measurement optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/54400.

Council of Science Editors:

He N. Saddle point techniques in convex composite and error-in-measurement optimization. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54400

Georgia Tech

4. Li, Yaxian. Lower bounds for integer programming problems.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/48959

► Solving real world problems with mixed integer programming (MIP) involves efforts in modeling and efficient algorithms. To solve a minimization MIP problem, a lower bound…
(more)

Subjects/Keywords: Lower bounds; Integer programming problems; Multi-dimensional knapsack problem; Algorithms; Knapsack problem (Mathematics); Integer programming

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Li, Y. (2013). Lower bounds for integer programming problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/48959

Chicago Manual of Style (16^{th} Edition):

Li, Yaxian. “Lower bounds for integer programming problems.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/48959.

MLA Handbook (7^{th} Edition):

Li, Yaxian. “Lower bounds for integer programming problems.” 2013. Web. 18 Apr 2021.

Vancouver:

Li Y. Lower bounds for integer programming problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/48959.

Council of Science Editors:

Li Y. Lower bounds for integer programming problems. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/48959

Georgia Tech

5. Mehta, Nishant A. On sparse representations and new meta-learning paradigms for representation learning.

Degree: PhD, Computer Science, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/52159

► Given the "right" representation, learning is easy. This thesis studies representation learning and meta-learning, with a special focus on sparse representations. Meta-learning is fundamental to…
(more)

Subjects/Keywords: Learning theory; Data-dependent complexity; Luckiness; Dictionary learning; Sparse coding; Lasso; Multi-task learning; Meta-learning; Learning to learn

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Mehta, N. A. (2013). On sparse representations and new meta-learning paradigms for representation learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52159

Chicago Manual of Style (16^{th} Edition):

Mehta, Nishant A. “On sparse representations and new meta-learning paradigms for representation learning.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/52159.

MLA Handbook (7^{th} Edition):

Mehta, Nishant A. “On sparse representations and new meta-learning paradigms for representation learning.” 2013. Web. 18 Apr 2021.

Vancouver:

Mehta NA. On sparse representations and new meta-learning paradigms for representation learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/52159.

Council of Science Editors:

Mehta NA. On sparse representations and new meta-learning paradigms for representation learning. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52159

Georgia Tech

6. Berlind, Christopher. New insights on the power of active learning.

Degree: PhD, Computer Science, 2015, Georgia Tech

URL: http://hdl.handle.net/1853/53948

► Traditional supervised machine learning algorithms are expected to have access to a large corpus of labeled examples, but the massive amount of data available in…
(more)

Subjects/Keywords: Machine learning; Learning theory; Active learning; Semi-supervised learning; Domain adaptation; Large margin learning

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Berlind, C. (2015). New insights on the power of active learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53948

Chicago Manual of Style (16^{th} Edition):

Berlind, Christopher. “New insights on the power of active learning.” 2015. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/53948.

MLA Handbook (7^{th} Edition):

Berlind, Christopher. “New insights on the power of active learning.” 2015. Web. 18 Apr 2021.

Vancouver:

Berlind C. New insights on the power of active learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/53948.

Council of Science Editors:

Berlind C. New insights on the power of active learning. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53948

7. Gui, Luyi. Managing and optimizing decentralized networks with resource sharing.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/47707

► Resource sharing is a common collaborative strategy used in practice. It has the potential to create synergistic value and leads to higher system efficiency. However,…
(more)

Subjects/Keywords: Legislation; Mechanism design; Resource sharing; Decentralized networks; Optimization; EPR; Game theory; Cooperative games (Mathematics); Self-interest; Mathematical optimization

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Gui, L. (2013). Managing and optimizing decentralized networks with resource sharing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47707

Chicago Manual of Style (16^{th} Edition):

Gui, Luyi. “Managing and optimizing decentralized networks with resource sharing.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/47707.

MLA Handbook (7^{th} Edition):

Gui, Luyi. “Managing and optimizing decentralized networks with resource sharing.” 2013. Web. 18 Apr 2021.

Vancouver:

Gui L. Managing and optimizing decentralized networks with resource sharing. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/47707.

Council of Science Editors:

Gui L. Managing and optimizing decentralized networks with resource sharing. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47707

8. Minsker, Stanislav. Non-asymptotic bounds for prediction problems and density estimation.

Degree: PhD, Mathematics, 2012, Georgia Tech

URL: http://hdl.handle.net/1853/44808

► This dissertation investigates the learning scenarios where a high-dimensional parameter has to be estimated from a given sample of fixed size, often smaller than the…
(more)

Subjects/Keywords: Active learning; Sparse recovery; Oracle inequality; Confidence bands; Infinite dictionary; Estimation theory Asymptotic theory; Estimation theory; Distribution (Probability theory); Prediction theory; Active learning; Algorithms; Mathematical optimization; Chebyshev approximation

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Minsker, S. (2012). Non-asymptotic bounds for prediction problems and density estimation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44808

Chicago Manual of Style (16^{th} Edition):

Minsker, Stanislav. “Non-asymptotic bounds for prediction problems and density estimation.” 2012. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/44808.

MLA Handbook (7^{th} Edition):

Minsker, Stanislav. “Non-asymptotic bounds for prediction problems and density estimation.” 2012. Web. 18 Apr 2021.

Vancouver:

Minsker S. Non-asymptotic bounds for prediction problems and density estimation. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/44808.

Council of Science Editors:

Minsker S. Non-asymptotic bounds for prediction problems and density estimation. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44808

9. Dudebout, Nicolas. Empirical-evidence equilibria in stochastic games.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/52205

► The objective of this research is to develop the framework of empirical-evidence equilibria (EEEs) in stochastic games. This framework was developed while attempting to design…
(more)

Subjects/Keywords: Equilibrium; Stochastic games; Bounded rationality

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Dudebout, N. (2014). Empirical-evidence equilibria in stochastic games. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52205

Chicago Manual of Style (16^{th} Edition):

Dudebout, Nicolas. “Empirical-evidence equilibria in stochastic games.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/52205.

MLA Handbook (7^{th} Edition):

Dudebout, Nicolas. “Empirical-evidence equilibria in stochastic games.” 2014. Web. 18 Apr 2021.

Vancouver:

Dudebout N. Empirical-evidence equilibria in stochastic games. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/52205.

Council of Science Editors:

Dudebout N. Empirical-evidence equilibria in stochastic games. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52205

10. Xiao, Ying. New tools for unsupervised learning.

Degree: PhD, Computer Science, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/52995

► In an unsupervised learning problem, one is given an unlabelled dataset and hopes to find some hidden structure; the prototypical example is clustering similar data.…
(more)

Subjects/Keywords: Tensor; Spectral decomposition; Unsupervised learning; Independent component analysis; Fourier transform; Gaussian mixture model; Feature selection

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Xiao, Y. (2014). New tools for unsupervised learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52995

Chicago Manual of Style (16^{th} Edition):

Xiao, Ying. “New tools for unsupervised learning.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/52995.

MLA Handbook (7^{th} Edition):

Xiao, Ying. “New tools for unsupervised learning.” 2014. Web. 18 Apr 2021.

Vancouver:

Xiao Y. New tools for unsupervised learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/52995.

Council of Science Editors:

Xiao Y. New tools for unsupervised learning. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52995

11. Ram, Parikshit. New paradigms for approximate nearest-neighbor search.

Degree: PhD, Computational Science and Engineering, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/49112

► Nearest-neighbor search is a very natural and universal problem in computer science. Often times, the problem size necessitates approximation. In this thesis, I present new…
(more)

Subjects/Keywords: Similarity search; Nearest-neighbor search; Computational geometry; Algorithms and analysis; Nearest neighbor analysis (Statistics); Approximation algorithms; Search theory

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Ram, P. (2013). New paradigms for approximate nearest-neighbor search. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49112

Chicago Manual of Style (16^{th} Edition):

Ram, Parikshit. “New paradigms for approximate nearest-neighbor search.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/49112.

MLA Handbook (7^{th} Edition):

Ram, Parikshit. “New paradigms for approximate nearest-neighbor search.” 2013. Web. 18 Apr 2021.

Vancouver:

Ram P. New paradigms for approximate nearest-neighbor search. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/49112.

Council of Science Editors:

Ram P. New paradigms for approximate nearest-neighbor search. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49112

12. Mac Dermed, Liam Charles. Value methods for efficiently solving stochastic games of complete and incomplete information.

Degree: PhD, Computer Science, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/50270

► Multi-agent reinforcement learning (MARL) poses the same planning problem as traditional reinforcement learning (RL): What actions over time should an agent take in order to…
(more)

Subjects/Keywords: Multi-agent planning; Game theory; Reinforcement learning; Reinforcement learning; Multiagent systems; Game theory

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Mac Dermed, L. C. (2013). Value methods for efficiently solving stochastic games of complete and incomplete information. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50270

Chicago Manual of Style (16^{th} Edition):

Mac Dermed, Liam Charles. “Value methods for efficiently solving stochastic games of complete and incomplete information.” 2013. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/50270.

MLA Handbook (7^{th} Edition):

Mac Dermed, Liam Charles. “Value methods for efficiently solving stochastic games of complete and incomplete information.” 2013. Web. 18 Apr 2021.

Vancouver:

Mac Dermed LC. Value methods for efficiently solving stochastic games of complete and incomplete information. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/50270.

Council of Science Editors:

Mac Dermed LC. Value methods for efficiently solving stochastic games of complete and incomplete information. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50270

Georgia Tech

13. Chen, Shang-Tse. AI-infused security: Robust defense by bridging theory and practice.

Degree: PhD, Computational Science and Engineering, 2019, Georgia Tech

URL: http://hdl.handle.net/1853/62296

► While Artificial Intelligence (AI) has tremendous potential as a defense against real-world cybersecurity threats, understanding the capabilities and robustness of AI remains a fundamental challenge.…
(more)

Subjects/Keywords: Security; Cybersecurity; Machine learning; Artificial Intelligence; Adversarial machine learning; Game theory; Boosting; Fire risk

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Chen, S. (2019). AI-infused security: Robust defense by bridging theory and practice. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62296

Chicago Manual of Style (16^{th} Edition):

Chen, Shang-Tse. “AI-infused security: Robust defense by bridging theory and practice.” 2019. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/62296.

MLA Handbook (7^{th} Edition):

Chen, Shang-Tse. “AI-infused security: Robust defense by bridging theory and practice.” 2019. Web. 18 Apr 2021.

Vancouver:

Chen S. AI-infused security: Robust defense by bridging theory and practice. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/62296.

Council of Science Editors:

Chen S. AI-infused security: Robust defense by bridging theory and practice. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62296

Georgia Tech

14. Liang, Yingyu. Modern aspects of unsupervised learning.

Degree: PhD, Computer Science, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/52282

► Unsupervised learning has become more and more important due to the recent explosion of data. Clustering, a key topic in unsupervised learning, is a well-studied…
(more)

Subjects/Keywords: Unsupervised learning; Clustering; Perturbation resilience; Distributed clustering; Community detection

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Liang, Y. (2014). Modern aspects of unsupervised learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52282

Chicago Manual of Style (16^{th} Edition):

Liang, Yingyu. “Modern aspects of unsupervised learning.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/52282.

MLA Handbook (7^{th} Edition):

Liang, Yingyu. “Modern aspects of unsupervised learning.” 2014. Web. 18 Apr 2021.

Vancouver:

Liang Y. Modern aspects of unsupervised learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/52282.

Council of Science Editors:

Liang Y. Modern aspects of unsupervised learning. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52282

15. Balavoine, Aurele. Mathematical analysis of a dynamical system for sparse recovery.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

URL: http://hdl.handle.net/1853/51882

► This thesis presents the mathematical analysis of a continuous-times system for sparse signal recovery. Sparse recovery arises in Compressed Sensing (CS), where signals of large…
(more)

Subjects/Keywords: Sparse recovery; Neural network; L1-minimization; Nonsmooth optimization; Compressed sensing; Tracking; ISTA; LCA; Sparse matrices; Signal processing Digital techniques; Mathematical optimization

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Balavoine, A. (2014). Mathematical analysis of a dynamical system for sparse recovery. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51882

Chicago Manual of Style (16^{th} Edition):

Balavoine, Aurele. “Mathematical analysis of a dynamical system for sparse recovery.” 2014. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/51882.

MLA Handbook (7^{th} Edition):

Balavoine, Aurele. “Mathematical analysis of a dynamical system for sparse recovery.” 2014. Web. 18 Apr 2021.

Vancouver:

Balavoine A. Mathematical analysis of a dynamical system for sparse recovery. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/51882.

Council of Science Editors:

Balavoine A. Mathematical analysis of a dynamical system for sparse recovery. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/51882

Georgia Tech

16. Karande, Chinmay. Algorithms and mechanism design for multi-agent systems.

Degree: PhD, Computing, 2010, Georgia Tech

URL: http://hdl.handle.net/1853/37229

► A scenario where multiple entities interact with a common environment to achieve individual and common goals either co-operatively or competitively can be classified as a…
(more)

Subjects/Keywords: Multi-agent systems; Online auction; Algorithms; Mechanism design; Submodular functions; Matroids

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Karande, C. (2010). Algorithms and mechanism design for multi-agent systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/37229

Chicago Manual of Style (16^{th} Edition):

Karande, Chinmay. “Algorithms and mechanism design for multi-agent systems.” 2010. Doctoral Dissertation, Georgia Tech. Accessed April 18, 2021. http://hdl.handle.net/1853/37229.

MLA Handbook (7^{th} Edition):

Karande, Chinmay. “Algorithms and mechanism design for multi-agent systems.” 2010. Web. 18 Apr 2021.

Vancouver:

Karande C. Algorithms and mechanism design for multi-agent systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2021 Apr 18]. Available from: http://hdl.handle.net/1853/37229.

Council of Science Editors:

Karande C. Algorithms and mechanism design for multi-agent systems. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/37229