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Discussion Panel
Tim van Erven · Wouter Koolen · Peter Grünwald · Shai Ben-David · Dylan Foster · Satyen Kale · Gergely Neu
Speakers unknown
Author Information
Tim van Erven (Leiden University)
Wouter Koolen (Centrum Wiskunde & Informatica)
Peter Grünwald (CWI and Leiden University)
Shai Ben-David (University of Waterloo)
Dylan Foster (Cornell University)
Satyen Kale (Yahoo Labs)
Gergely Neu (INRIA)
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2021 : Regret Minimization in Heavy-Tailed Bandits »
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2023 Poster: First- and Second-Order Bounds for Adversarial Linear Contextual Bandits »
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2023 Poster: Adaptive Selective Sampling for Online Prediction with Experts »
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2022 Poster: Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits »
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2021 Poster: SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs »
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2021 Poster: Learning with User-Level Privacy »
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2021 Poster: Breaking the centralized barrier for cross-device federated learning »
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2021 Poster: A/B/n Testing with Control in the Presence of Subpopulations »
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2021 Poster: Optimal Best-Arm Identification Methods for Tail-Risk Measures »
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2021 Poster: Online learning in MDPs with linear function approximation and bandit feedback. »
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2020 Poster: Estimating Training Data Influence by Tracing Gradient Descent »
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2020 Spotlight: Estimating Training Data Influence by Tracing Gradient Descent »
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2020 Poster: PAC-Bayes Learning Bounds for Sample-Dependent Priors »
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2020 Poster: A Unifying View of Optimism in Episodic Reinforcement Learning »
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2019 : Poster and Coffee Break 1 »
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2019 Poster: Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces »
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2019 Poster: Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates »
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2019 Poster: Beating SGD Saturation with Tail-Averaging and Minibatching »
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2019 Poster: Pure Exploration with Multiple Correct Answers »
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2019 Poster: Hypothesis Set Stability and Generalization »
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2019 Poster: Non-Asymptotic Pure Exploration by Solving Games »
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2018 Poster: Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling »
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2018 Poster: Contextual bandits with surrogate losses: Margin bounds and efficient algorithms »
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2018 Poster: Online Learning of Quantum States »
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2018 Poster: Adaptive Methods for Nonconvex Optimization »
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2018 Poster: Uniform Convergence of Gradients for Non-Convex Learning and Optimization »
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2017 : Peter Grünwald - A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity »
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2017 Poster: Random Permutation Online Isotonic Regression »
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2017 Poster: Spectrally-normalized margin bounds for neural networks »
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2017 Poster: Boltzmann Exploration Done Right »
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2017 Spotlight: Spectrally-normalized margin bounds for neural networks »
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2017 Poster: Monte-Carlo Tree Search by Best Arm Identification »
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2017 Poster: Parameter-Free Online Learning via Model Selection »
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2017 Spotlight: Parameter-Free Online Learning via Model Selection »
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2017 Spotlight: Monte-Carlo Tree Search by Best Arm Identification »
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2016 : Safe Probability »
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2016 : (Ir-)rationality of human decision making »
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2016 Poster: Learning in Games: Robustness of Fast Convergence »
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2016 Poster: Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning »
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2016 Poster: Hardness of Online Sleeping Combinatorial Optimization Problems »
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2016 Poster: Clustering with Same-Cluster Queries »
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2016 Poster: MetaGrad: Multiple Learning Rates in Online Learning »
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2016 Oral: MetaGrad: Multiple Learning Rates in Online Learning »
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2016 Oral: Clustering with Same-Cluster Queries »
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2015 : Domain Adaptation for Binary Classification »
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2015 : Adaptive Regret Bounds for Non-Stochastic Bandits »
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2015 : Optimal and Adaptive Algorithms for Online Boosting »
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2015 : Easy Data »
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2015 : Adaptive Online Learning »
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2015 : Clustering Is Easy When... »
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2015 : Learning Faster from Easy Data II: Introduction »
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2015 Workshop: Learning Faster from Easy Data II »
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2015 Poster: Adaptive Online Learning »
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2015 Poster: Minimax Time Series Prediction »
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2015 Poster: Explore no more: Improved high-probability regret bounds for non-stochastic bandits »
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2014 Workshop: From Bad Models to Good Policies (Sequential Decision Making under Uncertainty) »
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2014 Workshop: NIPS Workshop on Transactional Machine Learning and E-Commerce »
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2014 Poster: Efficient learning by implicit exploration in bandit problems with side observations »
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2014 Spotlight: Exploiting easy data in online optimization »
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2014 Poster: Learning the Learning Rate for Prediction with Expert Advice »
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2013 Workshop: Learning Faster From Easy Data »
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2013 Workshop: New Directions in Transfer and Multi-Task: Learning Across Domains and Tasks »
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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 »
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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 »
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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 »
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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 »
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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