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Jonathan Schneider
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2020 – today
- 2025
[c47]Maxwell Fishelson, Robert Kleinberg, Princewill Okoroafor, Renato Paes Leme, Jon Schneider, Yifeng Teng:
Full Swap Regret and Discretized Calibration. ALT 2025: 444-480- [i50]Maxwell Fishelson, Robert Kleinberg, Princewill Okoroafor, Renato Paes Leme, Jon Schneider, Yifeng Teng:
Full Swap Regret and Discretized Calibration. CoRR abs/2502.09332 (2025) - [i49]Adrian Müller, Jon Schneider, Stratis Skoulakis, Luca Viano, Volkan Cevher:
Best of Both Worlds: Regret Minimization versus Minimax Play. CoRR abs/2502.11673 (2025) - [i48]Eshwar Ram Arunachaleswaran, Natalie Collina, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Swap Regret and Correlated Equilibria Beyond Normal-Form Games. CoRR abs/2502.20229 (2025) - [i47]Mark Braverman, Jingyi Liu, Jieming Mao, Jon Schneider, Eric Xue:
A New Benchmark for Online Learning with Budget-Balancing Constraints. CoRR abs/2503.14796 (2025) - 2024
- [j7]Rad Niazadeh, Renato Paes Leme, Jon Schneider:
Bernoulli Factories for Flow-Based Polytopes. SIAM J. Discret. Math. 38(1): 726-742 (2024) - [j6]Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo:
Auto-Bidding and Auctions in Online Advertising: A Survey. SIGecom Exch. 22(1): 159-183 (2024) - [c46]Khashayar Gatmiry, Jon Schneider:
Adversarial Online Learning with Temporal Feedback Graphs. COLT 2024: 4548-4572 - [c45]Jon Schneider, Kiran Vodrahalli:
Online Learning with Bounded Recall. ICML 2024 - [c44]Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua R. Wang, S. Matthew Weinberg:
Contracting with a Learning Agent. NeurIPS 2024 - [c43]Renato Paes Leme, Georgios Piliouras, Jon Schneider:
Convergence of No-Swap-Regret Dynamics in Self-Play. NeurIPS 2024 - [c42]Renato Paes Leme
, Georgios Piliouras, Jon Schneider, Kelly Spendlove, Song Zuo:
Complex Dynamics in Autobidding Systems. EC 2024: 75-100 - [c41]Eshwar Ram Arunachaleswaran, Natalie Collina, Jon Schneider:
Pareto-Optimal Algorithms for Learning in Games. EC 2024: 490-510 - [c40]Rachitesh Kumar, Jon Schneider, Balasubramanian Sivan:
Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions. EC 2024: 893 - [c39]Guru Guruganesh, Jon Schneider, Joshua R. Wang:
Prior-Free Mechanism with Welfare Guarantees. WWW 2024: 135-143 - [i46]Jon Schneider, Julian Zimmert:
Optimal cross-learning for contextual bandits with unknown context distributions. CoRR abs/2401.01857 (2024) - [i45]Guru Guruganesh, Yoav Kolumbus, Jon Schneider, Inbal Talgam-Cohen, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Joshua R. Wang, S. Matthew Weinberg:
Contracting with a Learning Agent. CoRR abs/2401.16198 (2024) - [i44]Rachitesh Kumar, Jon Schneider, Balasubramanian Sivan:
Strategically-Robust Learning Algorithms for Bidding in First-Price Auctions. CoRR abs/2402.07363 (2024) - [i43]Eshwar Ram Arunachaleswaran, Natalie Collina, Jon Schneider:
Pareto-Optimal Algorithms for Learning in Games. CoRR abs/2402.09549 (2024) - [i42]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Rate-Preserving Reductions for Blackwell Approachability. CoRR abs/2406.07585 (2024) - [i41]Renato Paes Leme, Georgios Piliouras, Jon Schneider, Kelly Spendlove, Song Zuo:
Dynamical Analysis of Autobidding Systems. CoRR abs/2406.19350 (2024) - [i40]Khashayar Gatmiry, Jon Schneider:
Adversarial Online Learning with Temporal Feedback Graphs. CoRR abs/2407.00571 (2024) - [i39]Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro, Kshipra Bhawalkar, Yuan Deng, Zhe Feng, Gagan Goel, Christopher Liaw, Haihao Lu, Mohammad Mahdian, Jieming Mao, Aranyak Mehta, Vahab Mirrokni, Renato Paes Leme, Andrés Perlroth, Georgios Piliouras, Jon Schneider, Ariel Schvartzman, Balasubramanian Sivan, Kelly Spendlove, Yifeng Teng, Di Wang, Hanrui Zhang, Mingfei Zhao, Wennan Zhu, Song Zuo:
Auto-bidding and Auctions in Online Advertising: A Survey. CoRR abs/2408.07685 (2024) - [i38]Khashayar Gatmiry, Jon Schneider, Stefanie Jegelka:
Computing Optimal Regularizers for Online Linear Optimization. CoRR abs/2410.17336 (2024) - [i37]Eshwar Ram Arunachaleswaran, Natalie Collina, Jon Schneider:
Learning to Play Against Unknown Opponents. CoRR abs/2412.18297 (2024) - [i36]Constantinos Daskalakis, Gabriele Farina, Maxwell Fishelson, Charilaos Pipis, Jon Schneider:
Efficient Learning and Computation of Linear Correlated Equilibrium in General Convex Games. CoRR abs/2412.20291 (2024) - 2023
- [j5]Negin Golrezaei, Vahideh H. Manshadi, Jon Schneider, Shreyas Sekar:
Learning Product Rankings Robust to Fake Users. Oper. Res. 71(4): 1171-1196 (2023) - [j4]Santiago R. Balseiro, Negin Golrezaei, Mohammad Mahdian, Vahab Mirrokni, Jon Schneider:
Contextual Bandits with Cross-Learning. Math. Oper. Res. 48(3): 1607-1629 (2023) - [c38]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. ALT 2023: 471-509 - [c37]Bobby Kleinberg, Renato Paes Leme, Jon Schneider, Yifeng Teng:
U-Calibration: Forecasting for an Unknown Agent. COLT 2023: 5143-5145 - [c36]Maja Schneider, Peter Christen, Erhard Rahm, Jonathan Schneider, Lea Löffelmann:
Tuning the Utility-Privacy Trade-Off in Trajectory Data. EDBT 2023: 839-842 - [c35]Paul Duetting, Guru Guruganesh, Jon Schneider, Joshua Ruizhi Wang:
Optimal No-Regret Learning for One-Sided Lipschitz Functions. ICML 2023: 8836-8850 - [c34]William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? NeurIPS 2023 - [c33]Jon Schneider, Julian Zimmert:
Optimal cross-learning for contextual bandits with unknown context distributions. NeurIPS 2023 - [c32]Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao:
The Power of Menus in Contract Design. EC 2023: 818-848 - [c31]Gagan Goel, Renato Paes Leme, Jon Schneider, David Thompson, Hanrui Zhang:
Eligibility Mechanisms: Auctions Meet Information Retrieval. WWW 2023: 3541-3549 - [i35]Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Pseudonorm Approachability and Applications to Regret Minimization. CoRR abs/2302.01517 (2023) - [i34]William Brown, Jon Schneider, Kiran Vodrahalli:
Is Learning in Games Good for the Learners? CoRR abs/2305.19496 (2023) - [i33]Guru Guruganesh, Jon Schneider, Joshua R. Wang, Junyao Zhao:
The Power of Menus in Contract Design. CoRR abs/2306.12667 (2023) - [i32]Robert Kleinberg, Renato Paes Leme, Jon Schneider, Yifeng Teng:
U-Calibration: Forecasting for an Unknown Agent. CoRR abs/2307.00168 (2023) - [i31]Renato Paes Leme, Jon Schneider, Shuran Zheng:
Bayesian Conversations. CoRR abs/2307.08827 (2023) - [i30]Renato Paes Leme, Jon Schneider, Hanrui Zhang:
Nonbossy Mechanisms: Mechanism Design Robust to Secondary Goals. CoRR abs/2307.11967 (2023) - 2022
- [j3]Renato Paes Leme, Jon Schneider:
Contextual Search via Intrinsic Volumes. SIAM J. Comput. 51(4): 1096-1125 (2022) - [c30]Renato Paes Leme, Chara Podimata, Jon Schneider:
Corruption-Robust Contextual Search through Density Updates. COLT 2022: 3504-3505 - [c29]Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Strategizing against Learners in Bayesian Games. COLT 2022: 5221-5252 - [c28]Daniel Atzberger, Jonathan Schneider, Willy Scheibel, Matthias Trapp, Jürgen Döllner:
Evaluating Probabilistic Topic Models for Bug Triaging Tasks. ENASE (Selected Papers) 2022: 44-69 - [c27]Daniel Atzberger, Jonathan Schneider, Willy Scheibel, Daniel Limberger, Matthias Trapp, Jürgen Döllner:
Mining Developer Expertise from Bug Tracking Systems using the Author-topic Model. ENASE 2022: 107-118 - [c26]Gyunam Park, Aaron Küsters, Mara Tews, Cameron Pitsch, Jonathan Schneider, Wil M. P. van der Aalst:
Explainable Predictive Decision Mining for Operational Support. ICSOC Workshops 2022: 66-79 - [c25]Hossein Esfandiari, Vahab Mirrokni, Jon Schneider:
Anonymous Bandits for Multi-User Systems. NeurIPS 2022 - [i29]Renato Paes Leme, Jon Schneider:
Multiparameter Bernoulli Factories. CoRR abs/2202.07216 (2022) - [i28]Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan:
Strategizing against Learners in Bayesian Games. CoRR abs/2205.08562 (2022) - [i27]Jon Schneider, Kiran Vodrahalli:
History-Restricted Online Learning. CoRR abs/2205.14519 (2022) - [i26]Renato Paes Leme, Chara Podimata, Jon Schneider:
Corruption-Robust Contextual Search through Density Updates. CoRR abs/2206.07528 (2022) - [i25]Rad Niazadeh, Renato Paes Leme, Jon Schneider:
Bernoulli Factories for Flow-Based Polytopes. CoRR abs/2207.08965 (2022) - [i24]Hossein Esfandiari, Vahab Mirrokni, Jon Schneider:
Anonymous Bandits for Multi-User Systems. CoRR abs/2210.12198 (2022) - [i23]Gyunam Park, Aaron Küsters, Mara Tews, Cameron Pitsch, Jonathan Schneider, Wil M. P. van der Aalst:
Explainable Predictive Decision Mining for Operational Support. CoRR abs/2210.16786 (2022) - 2021
- [c24]Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye:
Reserve Price Optimization for First Price Auctions in Display Advertising. ICML 2021: 3230-3239 - [c23]Ehsan Emamjomeh-Zadeh, Renato Paes Leme, Jon Schneider, Balasubramanian Sivan:
Jointly Learning Prices and Product Features. IJCAI 2021: 2360-2366 - [c22]Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. NeurIPS 2021: 22498-22508 - [c21]Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. NeurIPS 2021: 29156-29167 - [c20]Mark Braverman, Jon Schneider, S. Matthew Weinberg:
Prior-free Dynamic Mechanism Design With Limited Liability. EC 2021: 204-223 - [c19]Negin Golrezaei, Vahideh H. Manshadi, Jon Schneider, Shreyas Sekar:
Learning Product Rankings Robust to Fake Users. EC 2021: 560-561 - [c18]Guru Guruganesh, Jon Schneider, Joshua R. Wang:
Contracts under Moral Hazard and Adverse Selection. EC 2021: 563-582 - [c17]Allen Liu, Renato Paes Leme, Martin Pál, Jon Schneider, Balasubramanian Sivan:
Variable Decomposition for Prophet Inequalities and Optimal Ordering. EC 2021: 692 - [c16]Allen Liu, Renato Paes Leme, Jon Schneider:
Optimal Contextual Pricing and Extensions. SODA 2021: 1059-1078 - [c15]Rad Niazadeh, Renato Paes Leme, Jon Schneider:
Combinatorial Bernoulli factories: matchings, flows, and other polytopes. STOC 2021: 833-846 - [i22]Mark Braverman, Jon Schneider, S. Matthew Weinberg:
Prior-free Dynamic Mechanism Design With Limited Liability. CoRR abs/2103.01868 (2021) - [i21]Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider:
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms. CoRR abs/2106.04819 (2021) - [i20]Guru Guruganesh, Allen Liu, Jon Schneider, Joshua R. Wang:
Margin-Independent Online Multiclass Learning via Convex Geometry. CoRR abs/2111.08057 (2021) - 2020
- [c14]Renato Paes Leme, Jon Schneider:
Costly Zero Order Oracles. COLT 2020: 3120-3132 - [c13]Allen Liu, Renato Paes Leme, Jon Schneider:
Myersonian Regression. NeurIPS 2020 - [i19]Allen Liu, Renato Paes Leme, Jon Schneider:
Contextual Search for General Hypothesis Classes. CoRR abs/2003.01703 (2020) - [i18]Allen Liu, Renato Paes Leme, Martin Pal, Jon Schneider, Balasubramanian Sivan:
Competing Optimally Against An Imperfect Prophet. CoRR abs/2004.10163 (2020) - [i17]Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye:
Reserve Price Optimization for First Price Auctions. CoRR abs/2006.06519 (2020) - [i16]Negin Golrezaei, Vahideh H. Manshadi, Jon Schneider, Shreyas Sekar:
Learning Product Rankings Robust to Fake Users. CoRR abs/2009.05138 (2020) - [i15]Guru Guruganesh, Jon Schneider, Joshua R. Wang:
Contracts under Moral Hazard and Adverse Selection. CoRR abs/2010.06742 (2020) - [i14]Rad Niazadeh, Renato Paes Leme, Jon Schneider:
Combinatorial Bernoulli Factories: Matchings, Flows and Other Polytopes. CoRR abs/2011.03865 (2020)
2010 – 2019
- 2019
- [c12]Mark Braverman, Jieming Mao, Jon Schneider, S. Matthew Weinberg:
Multi-armed Bandit Problems with Strategic Arms. COLT 2019: 383-416 - [c11]Sumegha Garg, Jon Schneider:
The Space Complexity of Mirror Games. ITCS 2019: 36:1-36:14 - [c10]Yuan Deng, Jon Schneider, Balasubramanian Sivan:
Strategizing against No-regret Learners. NeurIPS 2019: 1577-1585 - [c9]Yuan Deng, Jon Schneider, Balasubramanian Sivan:
Prior-Free Dynamic Auctions with Low Regret Buyers. NeurIPS 2019: 4804-4814 - [c8]Santiago R. Balseiro, Negin Golrezaei, Mohammad Mahdian, Vahab S. Mirrokni, Jon Schneider:
Contextual Bandits with Cross-Learning. NeurIPS 2019: 9676-9685 - [c7]Nihal Murali, Jon Schneider, Joel Levine, Graham W. Taylor:
Classification and Re-Identification of Fruit Fly Individuals Across Days With Convolutional Neural Networks. WACV 2019: 570-578 - [i13]Mark Braverman, Cristobal Rojas, Jonathan Schneider:
Space-bounded Church-Turing thesis and computational tractability of closed systems. CoRR abs/1905.03610 (2019) - [i12]Yuan Deng, Jon Schneider, Balasubramanian Sivan:
Strategizing against No-regret Learners. CoRR abs/1909.13861 (2019) - 2018
- [b1]Jonathan Schneider:
Learning Algorithms in Strategic Environments. Princeton University, USA, 2018 - [j2]Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider:
Optimal Instance Adaptive Algorithm for the Top-K Ranking Problem. IEEE Trans. Inf. Theory 64(9): 6139-6160 (2018) - [c6]Renato Paes Leme, Jon Schneider:
Contextual Search via Intrinsic Volumes. FOCS 2018: 268-282 - [c5]Jieming Mao, Renato Paes Leme, Jon Schneider:
Contextual Pricing for Lipschitz Buyers. NeurIPS 2018: 5648-5656 - [c4]Mark Braverman, Jieming Mao, Jon Schneider, S. Matthew Weinberg:
Selling to a No-Regret Buyer. EC 2018: 523-538 - [i11]Renato Paes Leme, Jon Schneider:
Contextual Search via Intrinsic Volumes. CoRR abs/1804.03195 (2018) - [i10]Santiago R. Balseiro, Negin Golrezaei, Mohammad Mahdian, Vahab S. Mirrokni, Jon Schneider:
Contextual Bandits with Cross-learning. CoRR abs/1809.09582 (2018) - 2017
- [c3]Jon Schneider, Ariel Schvartzman, S. Matthew Weinberg:
Condorcet-Consistent and Approximately Strategyproof Tournament Rules. ITCS 2017: 35:1-35:20 - [c2]Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider:
Competitive analysis of the top-K ranking problem. SODA 2017: 1245-1264 - [i9]Mark Braverman, Jieming Mao, Jon Schneider, S. Matthew Weinberg:
Multi-armed Bandit Problems with Strategic Arms. CoRR abs/1706.09060 (2017) - [i8]Sumegha Garg, Jon Schneider:
The space complexity of mirror games. CoRR abs/1710.02898 (2017) - [i7]Mark Braverman, Jieming Mao, Jon Schneider, S. Matthew Weinberg:
Selling to a No-Regret Buyer. CoRR abs/1711.09176 (2017) - 2016
- [c1]Mark Braverman, Jon Schneider:
Information Complexity Is Computable. ICALP 2016: 87:1-87:10 - [i6]Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider:
Competitive analysis of the top-K ranking problem. CoRR abs/1605.03933 (2016) - [i5]Jon Schneider, Ariel Schvartzman, S. Matthew Weinberg:
Condorcet-Consistent and Approximately Strategyproof Tournament Rules. CoRR abs/1605.09733 (2016) - 2015
- [i4]Mark Braverman, Jon Schneider:
Information complexity is computable. CoRR abs/1502.02971 (2015) - [i3]Mark Braverman, Cristobal Rojas, Jon Schneider:
Tight space-noise tradeoffs in computing the ergodic measure. CoRR abs/1508.05372 (2015) - [i2]Mark Braverman, Jon Schneider:
Information complexity is computable. Electron. Colloquium Comput. Complex. TR15 (2015) - 2014
- [j1]Jonathan Schneider:
Polynomial Sequences of Binomial-Type Arising in Graph Theory. Electron. J. Comb. 21(1): 1 (2014) - [i1]Erik D. Demaine, Nathan Pinsker, Jon Schneider:
Fast Dynamic Pointer Following via Link-Cut Trees. CoRR abs/1405.3739 (2014)
Coauthor Index
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