J. Abernethy

Most-cited papers

On Convergence and Stability of GANs
Naveen Kodali, James Hays, J. Abernethy, Z. Kira
2018672 citations
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Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization
J. Abernethy, Elad Hazan, A. Rakhlin
2008Annual Conference Computational Learning Theory395 citations
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Optimal Stragies and Minimax Lower Bounds for Online Convex Games
J. Abernethy, P. Bartlett, A. Rakhlin, Ambuj Tewari
2008Annual Conference Computational Learning Theory196 citations
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Dynamic Online Pricing with Incomplete Information Using Multiarmed Bandit Experiments
Kanishka Misra, Eric M. Schwartz, J. Abernethy
2019Marketing science (Providence, R.I.)174 citations
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Blackwell Approachability and No-Regret Learning are Equivalent
J. Abernethy, P. Bartlett, Elad Hazan
2010Annual Conference Computational Learning Theory145 citations
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Efficient Market Making via Convex Optimization, and a Connection to Online Learning
J. Abernethy, Yi-Ling Chen, Jennifer Wortman Vaughan
2013TEAC110 citations Open access
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A Stochastic View of Optimal Regret through Minimax Duality
J. Abernethy, Alekh Agarwal, P. Bartlett, A. Rakhlin
2009Annual Conference Computational Learning Theory99 citations
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Fighting Bandits with a New Kind of Smoothness
J. Abernethy, Chansoo Lee, Ambuj Tewari
2015Neural Information Processing Systems93 citations
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Interior-Point Methods for Full-Information and Bandit Online Learning
J. Abernethy, Elad Hazan, A. Rakhlin
2012IEEE Transactions on Information Theory91 citations
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How to Train Your DRAGAN
Naveen Kodali, J. Abernethy, James Hays, Z. Kira
2017arXiv.org89 citations
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Online Linear Optimization via Smoothing
J. Abernethy, Chansoo Lee, Abhinav Sinha, Ambuj Tewari
2014Annual Conference Computational Learning Theory89 citations
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Web spam identification through content and hyperlinks
J. Abernethy, O. Chapelle, Carlos Castillo
2008Adversarial Information Retrieval on the Web89 citations Open access
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Beating the adaptive bandit with high probability
J. Abernethy, A. Rakhlin
2009Information Theory and Applications Workshop83 citations
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Last-iterate convergence rates for min-max optimization
J. Abernethy, Kevin A. Lai, Andre Wibisono
2019arXiv.org74 citations
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An optimization-based framework for automated market-making
J. Abernethy, Yi-Ling Chen, Jennifer Wortman Vaughan
2010ACM Conference on Economics and Computation70 citations Open access
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Eliciting Consumer Preferences Using Robust Adaptive Choice Questionnaires
J. Abernethy, T. Evgeniou, Olivier Toubia, Jean-Philippe Vert
2008IEEE Transactions on Knowledge and Data Engineering68 citations
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Graph regularization methods for Web spam detection
J. Abernethy, O. Chapelle, Carlos Castillo
2010Machine-mediated learning65 citations Open access
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Active Sampling for Min-Max Fairness
J. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie H. Morgenstern +2 more
2020International Conference on Machine Learning61 citations
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A Collaborative Mechanism for Crowdsourcing Prediction Problems
J. Abernethy, Rafael M. Frongillo
2011Neural Information Processing Systems56 citations
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Faster Rates for Convex-Concave Games
J. Abernethy, Kevin A. Lai, K. Levy, Jun-Kun Wang
2018Annual Conference Computational Learning Theory51 citations
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Acceleration through Optimistic No-Regret Dynamics
Jun-Kun Wang, J. Abernethy
2018Neural Information Processing Systems49 citations
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Adaptive Market Making via Online Learning
J. Abernethy, Satyen Kale
2013Neural Information Processing Systems47 citations
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Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games
A. Cardoso, J. Abernethy, He Wang, Huan Xu
2019International Conference on Machine Learning45 citations
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Minimax Optimal Algorithms for Unconstrained Linear Optimization
H. B. McMahan, J. Abernethy
2013Neural Information Processing Systems45 citations
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On Frank-Wolfe and Equilibrium Computation
J. Abernethy, Jun-Kun Wang
2017Neural Information Processing Systems41 citations
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Low-Cost Learning via Active Data Procurement
J. Abernethy, Yi-Ling Chen, Chien-Ju Ho, Bo Waggoner
2015ACM Conference on Economics and Computation39 citations Open access
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WITCH: A NEW APPROACH TO WEB SPAM DETECTION
J. Abernethy
200839 citations
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Randomized Quantization is All You Need for Differential Privacy in Federated Learning
Yeojoon Youn, Zihao Hu, Juba Ziani, J. Abernethy
2023arXiv.org38 citations Open access
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No-regret dynamics in the Fenchel game: a unified framework for algorithmic convex optimization
Jun-Kun Wang, J. Abernethy, K. Levy
2021Mathematical programming38 citations Open access
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ActiveRemediation: The Search for Lead Pipes in Flint, Michigan
J. Abernethy, Alex Chojnacki, A. Farahi, Eric M. Schwartz +1 more
2018Knowledge Discovery and Data Mining36 citations
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A Data Science Approach to Understanding Residential Water Contamination in Flint
Alex Chojnacki, Chengyu Dai, A. Farahi, Guangsha Shi +4 more
2017Knowledge Discovery and Data Mining34 citations Open access
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A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
Jun-Kun Wang, Chi-Heng Lin, J. Abernethy
2020International Conference on Machine Learning32 citations
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Threshold Bandit, With and Without Censored Feedback
J. Abernethy, Kareem Amin, Rui-Hao Zhu
201629 citations
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Escaping Saddle Points Faster with Stochastic Momentum
Jun-Kun Wang, Chi-Heng Lin, J. Abernethy
2020International Conference on Learning Representations27 citations
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Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier
J. Abernethy, Elad Hazan
2015International Conference on Machine Learning26 citations
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Information aggregation in exponential family markets
J. Abernethy, Sindhu Kutty, Sébastien Lahaie, Rahul Sami
2014ACM Conference on Economics and Computation25 citations Open access
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Minimax option pricing meets black-scholes in the limit
J. Abernethy, Rafael M. Frongillo, Andre Wibisono
2012Symposium on the Theory of Computing24 citations
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A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks
J. Abernethy, Alekh Agarwal, T. Marinov, Manfred K. Warmuth
2023International Conference on Algorithmic Learning Theory23 citations Open access
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Learning Auctions with Robust Incentive Guarantees
J. Abernethy, Rachel Cummings, B. Kumar, Sam Taggart +1 more
2019Neural Information Processing Systems23 citations
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Utilizing high-dimensional features for real-time robotic applications: Reducing the curse of dimensionality for recursive Bayesian estimation
Jie Li, P. Ozog, J. Abernethy, Ryan M. Eustice +1 more
2016IEEE/RJS International Conference on Intelligent RObots and Systems21 citations
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A Market Framework for Eliciting Private Data
Bo Waggoner, Rafael M. Frongillo, J. Abernethy
2015Neural Information Processing Systems20 citations
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A Regularization Approach to Metrical Task Systems
J. Abernethy, P. Bartlett, Niv Buchbinder, I. Stanton
2010International Conference on Algorithmic Learning Theory19 citations
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Repeated Games against Budgeted Adversaries
J. Abernethy, Manfred K. Warmuth
2010Neural Information Processing Systems19 citations
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Fast Convergence of Fictitious Play for Diagonal Payoff Matrices
J. Abernethy, Kevin A. Lai, Andre Wibisono
2019ACM-SIAM Symposium on Discrete Algorithms18 citations Open access
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Online Learning via the Differential Privacy Lens
J. Abernethy, Young Hun Jung, Chansoo Lee, Audra McMillan +1 more
2017Neural Information Processing Systems16 citations
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How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal
J. Abernethy, P. Bartlett, Rafael M. Frongillo, Andre Wibisono
2013Neural Information Processing Systems16 citations
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Optimal strategies and minimax lower bounds for online convex games [Technical Report No. UCB/EECS-2008-19]
J. Abernethy, P. Bartlett, A. Rakhlin, Ambuj Tewari
200816 citations
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Observation-Free Attacks on Stochastic Bandits
Ying Xu, Bhuvesh Kumar, J. Abernethy
2021Neural Information Processing Systems14 citations
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A general volume-parameterized market making framework
J. Abernethy, Rafael M. Frongillo, Xiaolong Li, Jennifer Wortman Vaughan
2014ACM Conference on Economics and Computation14 citations
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Large-Scale Bandit Problems and KWIK Learning
J. Abernethy, Kareem Amin, Michael Kearns, M. Draief
2013International Conference on Machine Learning14 citations
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