@inproceedings{greenewald17action,
author = {Kristjan Greenewald and Ambuj Tewari and Susan A. Murphy and Predrag Klasnja},
title = {Action Centered Contextual Bandits},
booktitle = {Advances in Neural Information Processing Systems 30},
year = {2017},
note = {to appear}
}
@inproceedings{jung17online,
author = {Young Hun Jung and Jonathan Goetz and Ambuj Tewari},
title = {Online Multiclass Boosting},
booktitle = {Advances in Neural Information Processing Systems 30},
year = {2017},
note = {to appear}
}
@article{natarajan17cost,
author = {Nagarajan Natarajan and Inderjit S. Dhillon and Pradeep Ravikumar and Ambuj Tewari},
title = {Cost-Sensitive Learning with Noisy Labels},
journal = {Journal of Machine Learning Research},
year = {2017},
note = {to appear}
}
@article{chaudhuri17online,
author = {Sougata Chaudhuri and Ambuj Tewari},
title = {Online Learning to Rank with Top-k Feedback},
journal = {Journal of Machine Learning Research},
volume = {18},
number = {103},
pages = {1--50},
year = {2017},
pdf = {research/chaudhuri17online.pdf},
url = {http://jmlr.org/papers/v18/16-285.html}
}
@article{jain17partial,
author = {Prateek Jain and Inderjit S. Dhillon and Ambuj Tewari},
title = {Partial Hard Thresholding},
journal = {IEEE Transactions on Information Theory},
volume = {63},
number = {5},
year = {2017},
pages = {3029--3038},
url = {https://doi.org/10.1109/TIT.2017.2686880},
pdf = {research/jain17partial.pdf}
}
@incollection{tewari17ads,
author = {Ambuj Tewari and Susan A. Murphy},
title = {From Ads to Interventions: Contextual Bandits in Mobile Health},
booktitle = {Mobile Health: Sensors, Analytic Methods, and Applications},
publisher = {Springer},
year = {2017},
editor = {Jim Rehg and Susan A. Murphy and Santosh Kumar},
url = {https://www.springer.com/us/book/9783319513935},
pdf = {research/tewari17ads.pdf}
}
@article{faradonbeh16optimality,
author = {Mohamad Kazem Shirani Faradonbeh and Ambuj Tewari and George Michailidis},
title = {Optimality of Fast Matching Algorithms for Random Networks with Applications to Structural Controllability},
journal = {IEEE Transactions on Control of Network Systems},
year = {2016},
url = {https://doi.org/10.1109/TCNS.2016.2553366},
note = {to appear},
pdf = {research/faradonbeh16optimality.pdf}
}
@inproceedings{chaudhuri16phased,
author = {Sougata Chaudhuri and Ambuj Tewari},
title = {Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games},
booktitle = {Advances in Neural Information Processing Systems 29},
year = {2016},
pages = {2433--2441},
pdf = {research/chaudhuri16phased.pdf},
url = {https://papers.nips.cc/paper/6198-phased-exploration-with-greedy-exploitation-in-stochastic-combinatorial-partial-monitoring-games}
}
@article{nahum-shani16just-in-time,
author = {Inbal Nahum-Shani and Shawna N. Smith and Bonnie J. Spring and Linda M. Collins and Katie Witkiewitz and Ambuj Tewari and Susan A. Murphy},
title = {Just-in-Time Adaptive Interventions {(JITAIs)} in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support},
journal = {Annals of Behavioral Medicine},
year = {2016},
url = {http://dx.doi.org/10.1007/s12160-016-9830-8},
pdf = {research/nahum-shani16just-in-time.pdf},
note = {to appear}
}
@inproceedings{ramaswamy16mixture,
author = {Harish G. Ramaswamy and Clayton Scott and Ambuj Tewari},
title = {Mixture Proportion Estimation via Kernel Embeddings of Distributions},
booktitle = {Proceedings of the 33rd International Conference on Machine Learning},
series = {JMLR Workshop and Conference Proceedings},
volume = {48},
pages = {2052--2060},
year = {2016},
url = {http://jmlr.org/proceedings/papers/v48/ramaswamy16.html},
pdf = {research/ramaswamy16mixture.pdf}
}
@inproceedings{jiang16structural,
author = {Nan Jiang and Satinder Singh and Ambuj Tewari},
title = {On Structural Properties of {MDPs} that Bound Loss due to Shallow Planning},
booktitle = {Proceedings of the 25th International Joint Conference on Artificial Intelligence},
year = {2016},
pages = {1640--1647},
publisher = {AAAI Press},
url = {http://www.ijcai.org/Abstract/16/235},
pdf = {research/jiang16structural.pdf}
}
@incollection{abernethy16perturbation,
author = {Jacob Abernethy and Chansoo Lee and Ambuj Tewari},
title = {Perturbation Techniques in Online Learning and Optimization},
booktitle = {Perturbations, Optimization, and Statistics},
series = {Neural Information Processing Series},
publisher = {MIT Press},
year = {2016},
editor = {Tamir Hazan and George Papandreou and Daniel Tarlow},
chapter = {8},
pdf = {research/abernethy16perturbation.pdf},
url = {https://mitpress.mit.edu/books/perturbations-optimization-and-statistics}
}
@inproceedings{chaudhuri16online,
author = {Sougata Chaudhuri and Ambuj Tewari},
title = {Online Learning to Rank with Feedback at the Top},
booktitle = {Proceedings of the 19th International Conference on Artificial Intelligence and Statistics},
pages = {277--285},
series = {JMLR Workshop and Conference Proceedings},
volume = {51},
year = {2016},
pdf = {research/chaudhuri16online.pdf},
url = {http://jmlr.org/proceedings/papers/v51/chaudhuri16.html}
}
@article{liao16sample,
author = {Peng Liao and Predrag Klasnja and Ambuj Tewari and Susan A. Murphy},
title = {Sample Size Calculations for Micro-randomized Trials in mHealth},
journal = {Statistics in Medicine},
volume = {35},
number = {12},
pages = {1944--1971},
year = {2016},
url = {http://dx.doi.org/10.1002/sim.6847},
pdf = {research/liao16sample.pdf}
}
@article{klasnja15microrandomized,
author = {Predrag Klasnja and Eric B. Hekler and Saul Shiffman and Audrey
Boruvka and Daniel Almirall and Ambuj Tewari and Susan A. Murphy},
title = {Microrandomized trials: An experimental design for developing
just-in-time adaptive interventions},
journal = {Health Psychology},
volume = {34},
number = {Suppl},
month = {Dec},
pages = {1220--1228},
year = {2015},
url = {http://dx.doi.org/10.1037/hea0000305},
pdf = {research/klasnja15microrandomized.pdf}
}
@inproceedings{jain15predtron,
author = {Prateek Jain and Nagarajan Natarajan and Ambuj Tewari},
title = {Predtron: A Family of Online Algorithms for General Prediction Problems},
booktitle = {Advances in Neural Information Processing Systems 28},
pages = {1009--1017},
year = {2015},
url = {https://papers.nips.cc/paper/6000-predtron-a-family-of-online-algorithms-for-general-prediction-problems},
pdf = {research/jain15predtron.pdf}
}
@inproceedings{jain15alternating,
author = {Prateek Jain and Ambuj Tewari},
title = {Alternating Minimization for Regression Problems with Vector-valued Outputs},
booktitle = {Advances in Neural Information Processing Systems 28},
pages = {1126--1134},
year = {2015},
url = {https://papers.nips.cc/paper/5820-alternating-minimization-for-regression-problems-with-vector-valued-outputs},
pdf = {research/jain15alternating.pdf}
}
@inproceedings{abernethy15fighting,
author = {Jacob Abernethy and Chansoo Lee and Ambuj Tewari},
title = {Fighting Bandits with a New Kind of Smoothness},
booktitle = {Advances in Neural Information Processing Systems 28},
pages = {2188--2196},
year = {2015},
url = {https://papers.nips.cc/paper/6030-fighting-bandits-with-a-new-kind-of-smoothness},
pdf = {research/abernethy15fighting.pdf}
}
@inproceedings{ramaswamy15convex,
author = {Harish G. Ramaswamy and Ambuj Tewari and Shivani Agarwal},
title = {Convex Calibrated Surrogates for Hierarchical Classification},
booktitle = {Proceedings of the 32nd International Conference on Machine Learning},
series = {JMLR Workshop and Conference Proceedings},
volume = {37},
pages = {1852--1860},
year = {2015},
url = {http://jmlr.org/proceedings/papers/v37/ramaswamy15.html},
pdf = {research/ramaswamy15convex.pdf}
}
@inproceedings{tewari15generalization,
author = {Ambuj Tewari and Sougata Chaudhuri},
title = {Generalization error bounds for learning to rank: Does the length of document lists matter?},
booktitle = {Proceedings of the 32nd International Conference on Machine Learning},
series = {JMLR Workshop and Conference Proceedings},
volume = {37},
pages = {315--323},
year = {2015},
url = {http://jmlr.org/proceedings/papers/v37/tewari15.html},
pdf = {research/tewari15generalization.pdf}
}
@inproceedings{chaudhuri15online,
author = {Sougata Chaudhuri and Ambuj Tewari},
title = {Online Ranking with Top-1 Feedback},
booktitle = {Proceedings of the 18th International Conference on Artificial Intelligence and Statistics},
series = {JMLR Workshop and Conference Proceedings},
volume = {38},
pages = {129--137},
year = {2015},
note = {Honorable Mention, Best Student Paper Award},
pdf = {research/chaudhuri15online.pdf},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v38/chaudhuri15.html}
}
@article{rakhlin15online,
author = {Alexander Rakhlin and Karthik Sridharan and Ambuj Tewari},
title = {Online Learning via Sequential Complexities},
year = {2015},
journal = {Journal of Machine Learning Research},
volume = {16},
month = {Feb},
pages = {155--186},
pdf = {research/rakhlin15online.pdf},
url = {http://jmlr.org/papers/v16/rakhlin15a.html}
}
@article{rakhlin15sequential,
author = {Alexander Rakhlin and Karthik Sridharan and Ambuj Tewari},
title = {Sequential Complexities and Uniform Martingale Laws of Large Numbers},
journal = {Probability Theory and Related Fields},
year = {2015},
volume = {161},
number = {1--2},
pages = {111--153},
pdf = {research/rakhlin15sequential.pdf},
url = {http://dx.doi.org/10.1007/s00440-013-0545-5}
}
@inproceedings{jain14iterative,
author = {Prateek Jain and Ambuj Tewari and Purushottam Kar},
title = {On Iterative Hard Thresholding Methods for High-dimensional {M}-Estimation},
booktitle = {Advances in Neural Information Processing Systems 27},
pages = {685--693},
year = {2014},
pdf = {research/jain14iterative.pdf},
url = {http://papers.nips.cc/paper/5293-on-iterative-hard-thresholding-methods-for-high-dimensional-m-estimation}
}
@inproceedings{abernethy14online,
author = {Jacob Abernethy and Chansoo Lee and Abhinav Sinha and Ambuj Tewari},
title = {Online Linear Optimization via Smoothing},
series = {JMLR Workshop and Conference Proceedings},
volume = {35},
year = {2014},
pages = {807--823},
booktitle = {Proceedings of the 27th Annual Conference on Learning Theory},
pdf = {research/abernethy14online.pdf},
url = {http://jmlr.org/proceedings/papers/v35/abernethy14.html}
}
@article{chiang14prediction,
author = {Kai-Yang Chiang and Cho-Jui Hsieh and Nagarajan Natarajan and Ambuj Tewari and Inderjit S. Dhillon},
title = {Prediction and Clustering in Signed Networks: A Local to Global Perspective},
journal = {Journal of Machine Learning Research},
year = {2014},
volume = {15},
pages = {1177--1213},
month = {March},
pdf = {research/chiang14prediction.pdf},
url = {http://jmlr.org/papers/v15/chiang14a.html}
}
@incollection{tewari13learning,
author = {Ambuj Tewari and Peter L. Bartlett},
title = {Learning Theory},
booktitle = {Academic Press Library in Signal Processing: Volume 1 Signal Processing Theory and Machine Learning},
series = {Academic Press Library in Signal Processing},
volume = {1},
publisher = {Elsevier},
year = {2014},
editor = {Paulo S.R. Diniz and Johan A.K. Suykens and Rama Chellappa and Sergios Theodoridis},
chapter = {14},
pages = {775--816},
pdf = {research/tewari13learning.pdf},
url = {http://dx.doi.org/10.1016/B978-0-12-396502-8.00014-0}
}
@inproceedings{ramaswamy13convex,
author = {Harish G. Ramaswamy and Shivani Agarwal and Ambuj Tewari},
title = {Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses},
booktitle = {Advances in Neural Information Processing Systems 26},
pages = {1475--1483},
year = {2013},
pdf = {research/ramaswamy13convex.pdf},
url = {http://papers.nips.cc/paper/4906-convex-calibrated-surrogates-for-low-rank-loss-matrices-with-applications-to-subset-ranking-losses}
}
@inproceedings{natarajan13learning,
author = {Nagarajan Natarajan and Inderjit S. Dhillon and Pradeep Ravikumar and Ambuj Tewari},
title = {Learning with Noisy Labels},
booktitle = {Advances in Neural Information Processing Systems 26},
pages = {1196--1204},
year = {2013},
pdf = {research/natarajan13learning.pdf},
url = {http://papers.nips.cc/paper/5073-learning-with-noisy-labels}
}
@inproceedings{yang13robust,
author = {Eunho Yang and Ambuj Tewari and Pradeep Ravikumar},
title = {On Robust Estimation of High Dimensional Generalized Linear Models},
booktitle = {Proceedings of the 23rd International Joint Conference on Artificial Intelligence},
year = {2013},
pages = {1834--1840},
publisher = {AAAI Press},
url = {http://ijcai.org/Abstract/13/271},
pdf = {research/yang13robust.pdf}
}
@article{singh-blom13prediction,
author = {U. Martin Singh-Blom and Nagarajan Natarajan and Ambuj Tewari and John O. Woods and Inderjit S. Dhillon and Edward M. Marcotte},
title = {Prediction and validation of gene-disease associations using methods inspired by social network analyses},
year = {2013},
journal = {PLoS One},
volume = {8},
number = {5},
pages = {e58977},
url = {http://dx.doi.org/10.1371/journal.pone.0058977},
pdf = {research/singh-blom13prediction.pdf}
}
@article{saha13non-asymptotic,
author = {Ankan Saha and Ambuj Tewari},
title = {On the Non-asymptotic Convergence of Cyclic Coordinate Descent Methods},
year = {2013},
volume = {23},
number = {1},
journal = {SIAM Journal on Optimization},
pages = {576--601},
url = {http://dx.doi.org/10.1137/110840054},
pdf = {research/saha13non-asymptotic.pdf}
}
@inproceedings{scherrer12feature,
author = {Chad Scherrer and Ambuj Tewari and Mahantesh Halappanavar and David Haglin},
title = {Feature Clustering for Accelerating Parallel Coordinate Descent},
year = {2012},
booktitle = {Advances in Neural Information Processing Systems 25},
pages = {28--36},
pdf = {research/scherrer12feature.pdf},
url = {http://books.nips.cc/nips25.html}
}
@inproceedings{arora12deterministic,
author = {Raman Arora and Ofer Dekel and Ambuj Tewari},
title = {Deterministic {MDPs} with Adversarial Rewards and Bandit Feedback},
booktitle = {Proceedings of the 28th Annual Conference on Uncertainty in Artificial Intelligence},
year = {2012},
pages = {93--101},
publisher = {AUAI Press},
url = {http://uai.sis.pitt.edu/displayArticles.jsp?mmnu=1&smnu=1&proceeding_id=28},
pdf = {research/arora12deterministic.pdf}
}
@inproceedings{shukla12parallelizing,
author = {Shilpa Shukla and Matthew Lease and Ambuj Tewari},
title = {Parallelizing {L}ist{N}et Training using {S}park},
booktitle = {Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages = {1127--1128},
year = {2012},
url = {http://dx.doi.org/10.1145/2348283.2348502},
pdf = {research/shukla12parallelizing.pdf}
}
@inproceedings{arora12online,
author = {Raman Arora and Ofer Dekel and Ambuj Tewari},
title = {Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret},
booktitle = {Proceedings of the 29th International Conference on Machine Learning},
year = {2012},
pages = {1503--1510},
publisher = {Omnipress},
url = {http://icml.cc/discuss/2012/749.html},
pdf = {research/arora12online.pdf}
}
@inproceedings{kalyanakrishnan12pac,
author = {Shivaram Kalyanakrishnan and Ambuj Tewari and Peter Auer and Peter Stone},
title = {{PAC} Subset Selection in Stochastic Multi-armed Bandits},
booktitle = {Proceedings of the 29th International Conference on Machine Learning},
year = {2012},
pages = {655--662},
publisher = {Omnipress},
url = {http://icml.cc/discuss/2012/359.html},
pdf = {research/kalyanakrishnan12pac.pdf}
}
@inproceedings{scherrer12scaling,
author = {Chad Scherrer and Mahantesh Halappanavar and Ambuj Tewari and David Haglin},
title = {Scaling Up Coordinate Descent Algorithms for Large $l_1$ Regularization Problems},
booktitle = {Proceedings of the 29th International Conference on Machine Learning},
year = {2012},
pages = {1407--1414},
publisher = {Omnipress},
url = {http://icml.cc/discuss/2012/705.html},
pdf = {research/scherrer12scaling.pdf}
}
@article{kakade12regularization,
author = {Sham M. Kakade and Shai Shalev-Shwartz and Ambuj Tewari},
title = {Regularization Techniques for Learning with Matrices},
month = {June},
year = {2012},
journal = {Journal of Machine Learning Research},
volume = {13},
pages = {1865--1890},
pdf = {research/kakade12regularization.pdf},
url = {http://jmlr.csail.mit.edu/papers/v13/kakade12a.html}
}
@inproceedings{yang12perturbation,
author = {Eunho Yang and Ambuj Tewari and Pradeep Ravikumar},
title = {Perturbation based Large Margin Approach for Ranking},
booktitle = {Proceedings of the 15th International Conference on Artificial Intelligence and Statistics},
series = {JMLR Workshop and Conference Proceedings},
volume = {22},
year = {2012},
pages = {1358--1366},
pdf = {research/yang12perturbation.pdf},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v22/}
}
@inproceedings{srebro11universality,
author = {Nathan Srebro and Karthik Sridharan and Ambuj Tewari},
title = {On the Universality of Online Mirror Descent},
year = {2011},
booktitle = {Advances in Neural Information Processing Systems 24},
pages = {2645--2653},
note = {longer version available as arXiv:1107.4080},
pdf = {research/srebro11universality.pdf},
url = {http://books.nips.cc/nips24.html}
}
@inproceedings{jain11orthogonal,
author = {Prateek Jain and Ambuj Tewari and Inderjit S. Dhillon},
title = {Orthogonal Matching Pursuit with Replacement},
year = {2011},
booktitle = {Advances in Neural Information Processing Systems 24},
pages = {1215--1223},
note = {longer version available as arXiv:1106.2774},
pdf = {research/jain11orthogonal.pdf},
url = {http://books.nips.cc/nips24.html}
}
@inproceedings{tewari11greedy,
author = {Ambuj Tewari and Pradeep Ravikumar and Inderjit S. Dhillon},
title = {Greedy Algorithms for Structurally Constrained High Dimensional Problems},
year = {2011},
booktitle = {Advances in Neural Information Processing Systems 24},
pages = {882--890},
pdf = {research/tewari11greedy.pdf},
url = {http://books.nips.cc/nips24.html}
}
@inproceedings{dhillon11nearest,
author = {Inderjit S. Dhillon and Pradeep Ravikumar and Ambuj Tewari},
title = {Nearest Neighbor based Greedy Coordinate Descent},
year = {2011},
booktitle = {Advances in Neural Information Processing Systems 24},
pages = {2160--2168},
pdf = {research/dhillon11nearest.pdf},
url = {http://books.nips.cc/nips24.html}
}
@inproceedings{rakhlin11stochastic,
author = {Alexander Rakhlin and Karthik Sridharan and Ambuj Tewari},
title = {Online Learning: Stochastic, Constrained, and Smoothed Adversaries},
year = {2011},
booktitle = {Advances in Neural Information Processing Systems 24},
pages = {1764--1772},
note = {longer (but older) version available as arXiv:1104.5070},
pdf = {research/rakhlin11stochastic.pdf},
url = {http://books.nips.cc/nips24.html}
}
@inproceedings{chiang11exploiting,
author = {Kai-Yang Chiang and Nagarajan Natarajan and Ambuj Tewari and Inderjit S. Dhillon},
title = {Exploiting Longer Cycles for Link Prediction in Signed Networks},
booktitle = {Proceedings of the 20th ACM Conference on Information and Knowledge Management},
year = {2011},
pages = {1157--1162},
pdf = {research/chiang11exploiting.pdf},
url = {http://dx.doi.org/10.1145/2063576.2063742}
}
@article{shalev-shwartz11stochastic,
author = {Shai Shalev-Shwartz and Ambuj Tewari},
title = {Stochastic Methods for $l_1$ Regularized Loss Minimization},
journal = {Journal of Machine Learning Research},
volume = {12},
month = {June},
pages = {1865--1892},
year = {2011},
pdf = {research/shalev-shwartz11stochastic.pdf},
url = {http://jmlr.csail.mit.edu/papers/v12/shalev-shwartz11a.html}
}
@inproceedings{rakhlin11online,
author = {Alexander Rakhlin and Karthik Sridharan and Ambuj Tewari},
title = {Online Learning: Beyond Regret},
year = {2011},
booktitle = {Proceedings of the 24th Annual Conference on Learning Theory},
series = {JMLR Workshop and Conference Proceedings},
volume = {19},
pages = {559--594},
note = {Best Paper Award, longer version available as arXiv:1011.3168},
pdf = {research/rakhlin11online.pdf},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v19/}
}
@inproceedings{foster11complexity-based,
author = {Dean Foster and Alexander Rakhlin and Karthik Sridharan and Ambuj Tewari},
title = {Complexity-Based Approach to Calibration with Checking Rules},
year = {2011},
booktitle = {Proceedings of the 24th Annual Conference on Learning Theory},
series = {JMLR Workshop and Conference Proceedings},
volume = {19},
pages = {293--314},
pdf = {research/foster11complexity-based.pdf},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v19/}
}
@inproceedings{ravikumar11ndcg,
author = {Pradeep Ravikumar and Ambuj Tewari and Eunho Yang},
title = {On {NDCG} Consistency of Listwise Ranking Methods},
booktitle = {Proceedings of the 14th International Conference on Artificial Intelligence and Statistics},
series = {JMLR Workshop and Conference Proceedings},
volume = {15},
year = {2011},
pages = {618--626},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v15/},
pdf = {research/ravikumar11ndcg.pdf}
}
@inproceedings{saha11improved,
author = {Ankan Saha and Ambuj Tewari},
title = {Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback},
booktitle = {Proceedings of the 14th International Conference on Artificial Intelligence and Statistics},
series = {JMLR Workshop and Conference Proceedings},
volume = {15},
year = {2011},
pages = {636-642},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v15/},
pdf = {research/saha11improved.pdf}
}
@inproceedings{rakhlin10online,
author = {Alexander Rakhlin and Karthik Sridharan and Ambuj Tewari},
title = {Online Learning: Random Averages, Combinatorial Parameters, and Learnability},
year = {2010},
booktitle = {Advances in Neural Information Processing Systems 23},
pages = {1984--1992},
pdf = {research/rakhlin10online.pdf},
url = {http://books.nips.cc/nips23.html}
}
@inproceedings{srebro10smoothness,
author = {Nathan Srebro and Karthik Sridharan and Ambuj Tewari},
title = {Smoothness, Low Noise, and Fast Rates},
year = {2010},
booktitle = {Advances in Neural Information Processing Systems 23},
pages = {2199--2207},
pdf = {research/srebro10smoothness.pdf},
url = {http://books.nips.cc/nips23.html}
}
@inproceedings{duchi10composite,
author = {John Duchi and Shai Shalev-Shwartz and Yoram Singer and Ambuj Tewari},
title = {Composite Objective Mirror Descent},
year = {2010},
booktitle = {Proceedings of the 23rd Annual Conference on Learning Theory},
pages = {14--26},
publisher = {Omnipress},
url = {http://www.colt2010.org/papers.html},
pdf = {research/duchi10composite.pdf}
}
@inproceedings{sridharan10convex,
author = {Karthik Sridharan and Ambuj Tewari},
title = {Convex Games in {B}anach Spaces},
year = {2010},
booktitle = {Proceedings of the 23rd Annual Conference on Learning Theory},
pages = {1--13},
publisher = {Omnipress},
url = {http://www.colt2010.org/papers.html},
pdf = {research/sridharan10convex.pdf}
}
@inproceedings{kakade10learning,
author = {Sham M. Kakade and Ohad Shamir and Karthik Sridharan and Ambuj Tewari},
title = {Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity},
booktitle = {Proceedings of the 13th International Conference on Artificial Intelligence and Statistics},
series = {JMLR Workshop and Conference Proceedings},
volume = {9},
year = {2010},
pages = {381--388},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v9/},
pdf = {research/kakade10learning.pdf}
}
@inproceedings{bartlett09regal,
author = {Peter L. Bartlett and Ambuj Tewari},
title = {{REGAL}: A Regularization based Algorithm for Reinforcement Learning in Weakly Communicating {MDP}s},
booktitle = {Proceedings of the 25th Annual Conference on Uncertainty in Artificial Intelligence},
year = {2009},
pages = {35--42},
publisher = {AUAI Press},
url = {http://uai.sis.pitt.edu/displayArticles.jsp?mmnu=1&smnu=1&proceeding_id=25},
pdf = {research/bartlett09regal.pdf}
}
@inproceedings{shalev-shwartz09stochastic,
author = {Shai Shalev-Shwartz and Ambuj Tewari},
title = {Stochastic Methods for $l_1$ Regularized Loss Minimization},
booktitle = {Proceedings of the 26th International Conference on Machine Learning},
pages = {929--936},
year = {2009},
publisher = {ACM Press},
url = {http://doi.acm.org/10.1145/1553374.1553493},
pdf = {research/shalev-shwartz09stochastic.pdf}
}
@inproceedings{kakade09generalization,
author = {Sham M. Kakade and Ambuj Tewari},
title = {On the Generalization Ability of Online Strongly Convex Programming Algorithms},
booktitle = {Advances in Neural Information Processing Systems 21},
pages = {801--808},
year = {2009},
publisher = {MIT Press},
url = {http://books.nips.cc/nips21.html},
pdf = {research/kakade09generalization.pdf}
}
@inproceedings{kakade09complexity,
author = {Sham M. Kakade and Karthik Sridharan and Ambuj Tewari},
title = {On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization},
booktitle = {Advances in Neural Information Processing Systems 21},
pages = {793--800},
year = {2009},
publisher = {MIT Press},
url = {http://books.nips.cc/nips21.html},
pdf = {research/kakade09complexity.pdf}
}
@inproceedings{bartlett08high-probability,
author = {Peter L. Bartlett and Varsha Dani and Thomas P. Hayes and Sham M. Kakade and Alexander Rakhlin and Ambuj Tewari},
title = {High-probability Regret Bounds for Bandit Online Linear Optimization},
booktitle = {Proceedings of the 21st Annual Conference on Learning Theory},
pages = {335--342},
year = {2008},
publisher = {Omnipress},
url = {http://colt2008.cs.helsinki.fi/programme.shtml},
pdf = {research/bartlett08high-probability.pdf}
}
@inproceedings{abernethy08optimal,
author = {Jacob Abernethy and Peter L. Bartlett and Alexander Rakhlin and Ambuj Tewari},
title = {Optimal Strategies and Minimax Lower Bounds for Online Convex Games},
booktitle = {Proceedings of the 21st Annual Conference on Learning Theory},
pages = {414--424},
year = {2008},
publisher = {Omnipress},
url = {http://colt2008.cs.helsinki.fi/programme.shtml},
pdf = {research/abernethy08optimal.pdf}
}
@inproceedings{kakade08efficient,
author = {Sham M. Kakade and Shai Shalev-Shwartz and Ambuj Tewari},
title = {Efficient Bandit Algorithms for Online Multiclass Prediction},
booktitle = {Proceedings of the 25th International Conference on Machine Learning},
year = {2008},
pages = {440--447},
publisher = {ACM Press},
url = {http://doi.acm.org/10.1145/1390156.1390212},
pdf = {research/kakade08efficient.pdf}
}
@inproceedings{tewari08optimistic,
author = {Ambuj Tewari and Peter L. Bartlett},
title = {Optimistic Linear Programming gives Logarithmic Regret for Irreducible {MDPs}},
booktitle = {Advances in Neural Information Processing Systems 20},
year = {2008},
publisher = {MIT Press},
pages = {1505--1512},
url = {http://books.nips.cc/nips20.html},
pdf = {research/tewari08optimistic.pdf}
}
@inproceedings{tewari07bounded,
author = {Ambuj Tewari and Peter L. Bartlett},
title = {Bounded Parameter {M}arkov Decision Processes with Average Reward Criterion},
booktitle = {Proceedings of the 20th Annual Conference on Learning Theory},
year = {2007},
pages = {263--277},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {4539},
pdf = {research/tewari07bounded.pdf},
url = {http://dx.doi.org/10.1007/978-3-540-72927-3_20}
}
@article{tewari07consistency,
author = {Ambuj Tewari and Peter L. Bartlett},
title = {On the Consistency of Multiclass CLassification Methods},
journal = {Journal of Machine Learning Research},
year = {2007},
volume = {8},
month = {May},
pages = {1007--1025},
note = {(Invited paper)},
pdf = {research/tewari07consistency.pdf},
url = {http://jmlr.csail.mit.edu/papers/v8/tewari07a.html}
}
@article{bartlett07sparseness,
author = {Peter L. Bartlett and Ambuj Tewari},
title = {Sparseness vs Estimating Conditional Probabilities: Some Asymptotic Results},
journal = {Journal of Machine Learning Research},
year = {2007},
volume = {8},
month = {Apr},
pages = {775--790},
pdf = {research/bartlett07sparseness.pdf},
url = {http://jmlr.csail.mit.edu/papers/v8/bartlett07a.html}
}
@inproceedings{bartlett07sample,
author = {Peter L. Bartlett and Ambuj Tewari},
title = {Sample Complexity of Policy Search with Known Dynamics},
year = {2007},
pages = {97--104},
booktitle = {Advances in Neural Information Processing Systems 19},
publisher = {MIT Press},
pdf = {research/bartlett07sample.pdf},
url = {http://books.nips.cc/nips19.html}
}
@inproceedings{tewari05consistency,
author = {Ambuj Tewari and Peter L. Bartlett},
title = {On the Consistency of Multiclass Classification Methods},
booktitle = {Proceedings of the 18th Annual Conference on Learning Theory},
year = {2005},
pages = {147--153},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {3559},
note = {Student Paper Award},
pdf = {research/tewari05consistency.pdf},
url = {http://dx.doi.org/10.1007/11503415_10}
}
@inproceedings{bartlett04sparseness,
author = {Peter L. Bartlett and Ambuj Tewari},
title = {Sparseness versus Estimating Conditional Probabilities: Some Asymptotic Results},
booktitle = {Proceedings of the 17th Annual Conference on Learning Theory},
year = {2004},
pages = {564--578},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {3120},
pdf = {research/bartlett04sparseness.pdf},
url = {http://springerlink.metapress.com/link.asp?id=0p46xx6w26qdwpqx}
}
@inproceedings{tewari02parallel,
author = {Ambuj Tewari and Utkarsh Srivastava and Phalguni Gupta},
title = {A Parallel {DFA} Minimization Algorithm},
booktitle = {Proceedings of the 9th International Conference on High Performance Computing},
year = {2002},
pages = {34--40},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {2552},
pdf = {research/tewari02parallel.pdf},
url = {http://springerlink.metapress.com/link.asp?id=kkcx5q70epjdnq5c}
}
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