More from the Same Authors

• 2021 : Regret Minimization in Heavy-Tailed Bandits »
  Shubhada Agrawal · Sandeep Juneja · Wouter Koolen
• 2023 Poster: First- and Second-Order Bounds for Adversarial Linear Contextual Bandits »
  Iuliia Olkhovskaia · Jack Mayo · Tim van Erven · Gergely Neu · Chen-Yu Wei
• 2023 Poster: Efficient Model-Free Exploration in Low-Rank MDPs »
  Zak Mhammedi · Adam Block · Dylan J Foster · Alexander Rakhlin
• 2023 Poster: Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games »
  Hedi Hadiji · Sarah Sachs · Tim van Erven · Wouter Koolen
• 2023 Poster: Model-Free Reinforcement Learning with the Decision-Estimation Coefficient »
  Dylan J Foster · Noah Golowich · Jian Qian · Alexander Rakhlin · Ayush Sekhari
• 2023 Poster: Adaptive Selective Sampling for Online Prediction with Experts »
  Rui Castro · Fredrik Hellström · Tim van Erven
• 2022 Poster: Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits »
  Gergely Neu · Iuliia Olkhovskaia · Matteo Papini · Ludovic Schwartz
• 2022 Poster: Luckiness in Multiscale Online Learning »
  Wouter Koolen · Muriel F. Pérez-Ortiz
• 2022 Poster: Proximal Point Imitation Learning »
  Luca Viano · Angeliki Kamoutsi · Gergely Neu · Igor Krawczuk · Volkan Cevher
• 2022 Poster: Interaction-Grounded Learning with Action-Inclusive Feedback »
  Tengyang Xie · Akanksha Saran · Dylan J Foster · Lekan Molu · Ida Momennejad · Nan Jiang · Paul Mineiro · John Langford
• 2022 Poster: Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness »
  Sarah Sachs · Hedi Hadiji · Tim van Erven · Cristóbal Guzmán
• 2022 Poster: Reproducibility in Optimization: Theoretical Framework and Limits »
  Kwangjun Ahn · Prateek Jain · Ziwei Ji · Satyen Kale · Praneeth Netrapalli · Gil I Shamir
• 2022 Poster: Understanding the Eluder Dimension »
  Gene Li · Pritish Kamath · Dylan J Foster · Nati Srebro
• 2022 Poster: From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent »
  Christopher De Sa · Satyen Kale · Jason Lee · Ayush Sekhari · Karthik Sridharan
• 2022 Poster: On the Complexity of Adversarial Decision Making »
  Dylan J Foster · Alexander Rakhlin · Ayush Sekhari · Karthik Sridharan
• 2021 Poster: SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs »
  Ayush Sekhari · Karthik Sridharan · Satyen Kale
• 2021 Poster: Learning with User-Level Privacy »
  Daniel Levy · Ziteng Sun · Kareem Amin · Satyen Kale · Alex Kulesza · Mehryar Mohri · Ananda Theertha Suresh
• 2021 Poster: Breaking the centralized barrier for cross-device federated learning »
  Sai Praneeth Karimireddy · Martin Jaggi · Satyen Kale · Mehryar Mohri · Sashank Reddi · Sebastian Stich · Ananda Theertha Suresh
• 2021 Poster: A/B/n Testing with Control in the Presence of Subpopulations »
  Yoan Russac · Christina Katsimerou · Dennis Bohle · Olivier Cappé · Aurélien Garivier · Wouter Koolen
• 2021 Poster: Optimal Best-Arm Identification Methods for Tail-Risk Measures »
  Shubhada Agrawal · Wouter Koolen · Sandeep Juneja
• 2021 Poster: Online learning in MDPs with linear function approximation and bandit feedback. »
  Gergely Neu · Iuliia Olkhovskaia
• 2020 Poster: Estimating Training Data Influence by Tracing Gradient Descent »
  Garima Pruthi · Frederick Liu · Satyen Kale · Mukund Sundararajan
• 2020 Spotlight: Estimating Training Data Influence by Tracing Gradient Descent »
  Garima Pruthi · Frederick Liu · Satyen Kale · Mukund Sundararajan
• 2020 Poster: PAC-Bayes Learning Bounds for Sample-Dependent Priors »
  Pranjal Awasthi · Satyen Kale · Stefani Karp · Mehryar Mohri
• 2020 Poster: A Unifying View of Optimism in Episodic Reinforcement Learning »
  Gergely Neu · Ciara Pike-Burke
• 2019 : Poster and Coffee Break 1 »
  Aaron Sidford · Aditya Mahajan · Alejandro Ribeiro · Alex Lewandowski · Ali H Sayed · Ambuj Tewari · Angelika Steger · Anima Anandkumar · Asier Mujika · Hilbert J Kappen · Bolei Zhou · Byron Boots · Chelsea Finn · Chen-Yu Wei · Chi Jin · Ching-An Cheng · Christina Yu · Clement Gehring · Craig Boutilier · Dahua Lin · Daniel McNamee · Daniel Russo · David Brandfonbrener · Denny Zhou · Devesh Jha · Diego Romeres · Doina Precup · Dominik Thalmeier · Eduard Gorbunov · Elad Hazan · Elena Smirnova · Elvis Dohmatob · Emma Brunskill · Enrique Munoz de Cote · Ethan Waldie · Florian Meier · Florian Schaefer · Ge Liu · Gergely Neu · Haim Kaplan · Hao Sun · Hengshuai Yao · Jalaj Bhandari · James A Preiss · Jayakumar Subramanian · Jiajin Li · Jieping Ye · Jimmy Smith · Joan Bas Serrano · Joan Bruna · John Langford · Jonathan Lee · Jose A. Arjona-Medina · Kaiqing Zhang · Karan Singh · Yuping Luo · Zafarali Ahmed · Zaiwei Chen · Zhaoran Wang · Zhizhong Li · Zhuoran Yang · Ziping Xu · Ziyang Tang · Yi Mao · David Brandfonbrener · Shirli Di-Castro · Riashat Islam · Zuyue Fu · Abhishek Naik · Saurabh Kumar · Benjamin Petit · Angeliki Kamoutsi · Simone Totaro · Arvind Raghunathan · Rui Wu · Donghwan Lee · Dongsheng Ding · Alec Koppel · Hao Sun · Christian Tjandraatmadja · Mahdi Karami · Jincheng Mei · Chenjun Xiao · Junfeng Wen · Zichen Zhang · Ross Goroshin · Mohammad Pezeshki · Jiaqi Zhai · Philip Amortila · Shuo Huang · Mariya Vasileva · El houcine Bergou · Adel Ahmadyan · Haoran Sun · Sheng Zhang · Lukas Gruber · Yuanhao Wang · Tetiana Parshakova
• 2019 Poster: Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces »
  Chuan Guo · Ali Mousavi · Xiang Wu · Daniel Holtmann-Rice · Satyen Kale · Sashank Reddi · Sanjiv Kumar
• 2019 Poster: PAC-Bayes Un-Expected Bernstein Inequality »
  Zakaria Mhammedi · Peter Grünwald · Benjamin Guedj
• 2019 Poster: Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates »
  Carlos Riquelme · Hugo Penedones · Damien Vincent · Hartmut Maennel · Sylvain Gelly · Timothy A Mann · Andre Barreto · Gergely Neu
• 2019 Poster: Beating SGD Saturation with Tail-Averaging and Minibatching »
  Nicole Muecke · Gergely Neu · Lorenzo Rosasco
• 2019 Poster: Pure Exploration with Multiple Correct Answers »
  Rémy Degenne · Wouter Koolen
• 2019 Poster: Hypothesis Set Stability and Generalization »
  Dylan Foster · Spencer Greenberg · Satyen Kale · Haipeng Luo · Mehryar Mohri · Karthik Sridharan
• 2019 Poster: Non-Asymptotic Pure Exploration by Solving Games »
  Rémy Degenne · Wouter Koolen · Pierre Ménard
• 2018 Poster: Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling »
  Emilie Kaufmann · Wouter Koolen · Aurélien Garivier
• 2018 Poster: Contextual bandits with surrogate losses: Margin bounds and efficient algorithms »
  Dylan Foster · Akshay Krishnamurthy
• 2018 Poster: Online Learning of Quantum States »
  Scott Aaronson · Xinyi Chen · Elad Hazan · Satyen Kale · Ashwin Nayak
• 2018 Poster: Adaptive Methods for Nonconvex Optimization »
  Manzil Zaheer · Sashank Reddi · Devendra S Sachan · Satyen Kale · Sanjiv Kumar
• 2018 Poster: Uniform Convergence of Gradients for Non-Convex Learning and Optimization »
  Dylan Foster · Ayush Sekhari · Karthik Sridharan
• 2017 : Peter Grünwald - A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity »
  Peter Grünwald
• 2017 Poster: Random Permutation Online Isotonic Regression »
  Wojciech Kotlowski · Wouter Koolen · Alan Malek
• 2017 Poster: Spectrally-normalized margin bounds for neural networks »
  Peter Bartlett · Dylan J Foster · Matus Telgarsky
• 2017 Poster: Boltzmann Exploration Done Right »
  Nicolò Cesa-Bianchi · Claudio Gentile · Gergely Neu · Gabor Lugosi
• 2017 Spotlight: Spectrally-normalized margin bounds for neural networks »
  Peter Bartlett · Dylan J Foster · Matus Telgarsky
• 2017 Poster: Monte-Carlo Tree Search by Best Arm Identification »
  Emilie Kaufmann · Wouter Koolen
• 2017 Poster: Parameter-Free Online Learning via Model Selection »
  Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan
• 2017 Spotlight: Parameter-Free Online Learning via Model Selection »
  Dylan J Foster · Satyen Kale · Mehryar Mohri · Karthik Sridharan
• 2017 Spotlight: Monte-Carlo Tree Search by Best Arm Identification »
  Emilie Kaufmann · Wouter Koolen
• 2016 : Safe Probability »
  Peter Grünwald
• 2016 : (Ir-)rationality of human decision making »
  Peter Grünwald
• 2016 Poster: Learning in Games: Robustness of Fast Convergence »
  Dylan Foster · zhiyuan li · Thodoris Lykouris · Karthik Sridharan · Eva Tardos
• 2016 Poster: Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning »
  Wouter Koolen · Peter Grünwald · Tim van Erven
• 2016 Poster: Hardness of Online Sleeping Combinatorial Optimization Problems »
  Satyen Kale · Chansoo Lee · David Pal
• 2016 Poster: Clustering with Same-Cluster Queries »
  Hassan Ashtiani · Shrinu Kushagra · Shai Ben-David
• 2016 Poster: MetaGrad: Multiple Learning Rates in Online Learning »
  Tim van Erven · Wouter Koolen
• 2016 Oral: MetaGrad: Multiple Learning Rates in Online Learning »
  Tim van Erven · Wouter Koolen
• 2016 Oral: Clustering with Same-Cluster Queries »
  Hassan Ashtiani · Shrinu Kushagra · Shai Ben-David
• 2015 : Domain Adaptation for Binary Classification »
  Shai Ben-David
• 2015 : Adaptive Regret Bounds for Non-Stochastic Bandits »
  Gergely Neu
• 2015 : Optimal and Adaptive Algorithms for Online Boosting »
  Satyen Kale
• 2015 : Easy Data »
  Peter Grünwald
• 2015 : Adaptive Online Learning »
  Dylan Foster
• 2015 : Clustering Is Easy When... »
  Shai Ben-David
• 2015 : Learning Faster from Easy Data II: Introduction »
  Tim van Erven
• 2015 Workshop: Learning Faster from Easy Data II »
  Tim van Erven · Wouter Koolen
• 2015 Poster: Adaptive Online Learning »
  Dylan Foster · Alexander Rakhlin · Karthik Sridharan
• 2015 Spotlight: Adaptive Online Learning »
  Dylan Foster · Alexander Rakhlin · Karthik Sridharan
• 2015 Poster: Online Gradient Boosting »
  Alina Beygelzimer · Elad Hazan · Satyen Kale · Haipeng Luo
• 2015 Poster: Minimax Time Series Prediction »
  Wouter Koolen · Alan Malek · Peter Bartlett · Yasin Abbasi Yadkori
• 2015 Poster: Explore no more: Improved high-probability regret bounds for non-stochastic bandits »
  Gergely Neu
• 2014 Workshop: From Bad Models to Good Policies (Sequential Decision Making under Uncertainty) »
  Odalric-Ambrym Maillard · Timothy A Mann · Shie Mannor · Jeremie Mary · Laurent Orseau · Thomas Dietterich · Ronald Ortner · Peter Grünwald · Joelle Pineau · Raphael Fonteneau · Georgios Theocharous · Esteban D Arcaute · Christos Dimitrakakis · Nan Jiang · Doina Precup · Pierre-Luc Bacon · Marek Petrik · Aviv Tamar
• 2014 Workshop: NIPS Workshop on Transactional Machine Learning and E-Commerce »
  David Parkes · David H Wolpert · Jennifer Wortman Vaughan · Jacob D Abernethy · Amos Storkey · Mark Reid · Ping Jin · Nihar Bhadresh Shah · Mehryar Mohri · Luis E Ortiz · Robin Hanson · Aaron Roth · Satyen Kale · Sebastien Lahaie
• 2014 Poster: Exploiting easy data in online optimization »
  Amir Sani · Gergely Neu · Alessandro Lazaric
• 2014 Poster: Efficient learning by implicit exploration in bandit problems with side observations »
  Tomáš Kocák · Gergely Neu · Michal Valko · Remi Munos
• 2014 Spotlight: Exploiting easy data in online optimization »
  Amir Sani · Gergely Neu · Alessandro Lazaric
• 2014 Poster: Online combinatorial optimization with stochastic decision sets and adversarial losses »
  Gergely Neu · Michal Valko
• 2014 Poster: Efficient Minimax Strategies for Square Loss Games »
  Wouter M Koolen · Alan Malek · Peter Bartlett
• 2014 Poster: Learning the Learning Rate for Prediction with Expert Advice »
  Wouter M Koolen · Tim van Erven · Peter Grünwald
• 2013 Workshop: Learning Faster From Easy Data »
  Peter Grünwald · Wouter M Koolen · Sasha Rakhlin · Nati Srebro · Alekh Agarwal · Karthik Sridharan · Tim van Erven · Sebastien Bubeck
• 2013 Workshop: New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks »
  Urun Dogan · Marius Kloft · Tatiana Tommasi · Francesco Orabona · Massimiliano Pontil · Sinno Jialin Pan · Shai Ben-David · Arthur Gretton · Fei Sha · Marco Signoretto · Rajhans Samdani · Yun-Qian Miao · Mohammad Gheshlaghi azar · Ruth Urner · Christoph Lampert · Jonathan How
• 2013 Workshop: Large Scale Matrix Analysis and Inference »
  Reza Zadeh · Gunnar Carlsson · Michael Mahoney · Manfred K. Warmuth · Wouter M Koolen · Nati Srebro · Satyen Kale · Malik Magdon-Ismail · Ashish Goel · Matei A Zaharia · David Woodruff · Ioannis Koutis · Benjamin Recht
• 2013 Poster: The Pareto Regret Frontier »
  Wouter M Koolen
• 2013 Poster: Adaptive Market Making via Online Learning »
  Jacob D Abernethy · Satyen Kale
• 2013 Oral: Adaptive Market Making via Online Learning »
  Jacob D Abernethy · Satyen Kale
• 2013 Poster: Online learning in episodic Markovian decision processes by relative entropy policy search »
  Alexander Zimin · Gergely Neu
• 2012 Poster: Mixability in Statistical Learning »
  Tim van Erven · Peter Grünwald · Mark Reid · Robert Williamson
• 2012 Poster: Putting Bayes to sleep »
  Wouter M Koolen · Dmitri Adamskiy · Manfred K. Warmuth
• 2012 Spotlight: Putting Bayes to sleep »
  Wouter M Koolen · Dmitri Adamskiy · Manfred K. Warmuth
• 2011 Poster: Adaptive Hedge »
  Tim van Erven · Peter Grünwald · Wouter M Koolen · Steven D Rooij
• 2011 Poster: Learning Eigenvectors for Free »
  Wouter M Koolen · Wojciech Kotlowski · Manfred K. Warmuth
• 2011 Poster: Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction »
  Elad Hazan · Satyen Kale
• 2010 Spotlight: Online Markov Decision Processes under Bandit Feedback »
  Gergely Neu · András György · András Antos · Csaba Szepesvari
• 2010 Poster: Online Markov Decision Processes under Bandit Feedback »
  Gergely Neu · András György · Csaba Szepesvari · András Antos
• 2010 Poster: Non-Stochastic Bandit Slate Problems »
  Satyen Kale · Lev Reyzin · Robert E Schapire
• 2010 Poster: Towards Property-Based Classification of Clustering Paradigms »
  Margareta Ackerman · Shai Ben-David · David R Loker
• 2009 Workshop: Clustering: Science or art? Towards principled approaches »
  Margareta Ackerman · Shai Ben-David · Avrim Blum · Isabelle Guyon · Ulrike von Luxburg · Robert Williamson · Reza Zadeh
• 2009 Poster: On Stochastic and Worst-case Models for Investing »
  Elad Hazan · Satyen Kale
• 2009 Oral: On Stochastic and Worst-case Models for Investing »
  Elad Hazan · Satyen Kale
• 2009 Poster: Beyond Convexity: Online Submodular Minimization »
  Elad Hazan · Satyen Kale
• 2008 Workshop: New Challanges in Theoretical Machine Learning: Data Dependent Concept Spaces »
  Maria-Florina F Balcan · Shai Ben-David · Avrim Blum · Kristiaan Pelckmans · John Shawe-Taylor
• 2008 Poster: Measures of Clustering Quality: A Working Set of Axioms for Clustering »
  Shai Ben-David · Margareta Ackerman
• 2008 Oral: Measures of Clustering Quality: A Working Set of Axioms for Clustering »
  Shai Ben-David · Margareta Ackerman
• 2007 Spotlight: Catching Up Faster in Bayesian Model Selection and Model Averaging »
  Tim van Erven · Peter Grünwald · Steven de Rooij
• 2007 Poster: Catching Up Faster in Bayesian Model Selection and Model Averaging »
  Tim van Erven · Peter Grünwald · Steven de Rooij
• 2007 Poster: Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria »
  Elad Hazan · Satyen Kale
• 2006 Poster: Analysis of Representations for Domain Adaptation »
  John Blitzer · Shai Ben-David · Yacov Crammer · Fernando Pereira