Tim van Erven - RankMe

62 papers A* 14A 2B 4Journal 36Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An Improved Algorithm for Adversarial Linear Contextual Bandits via Reduction. CoRR Tim van Erven, Jack J. Mayo, Julia Olkhovskaya, Chen-Yu Wei
2025	B	`conf`	An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems. ALT Sarah Sachs, Hédi Hadiji, Tim van Erven, Mathias Staudigl
2025	J	`jnl`	Nearly Minimax Discrete Distribution Estimation in Kullback-Leibler Divergence with High Probability. CoRR Dirk van der Hoeven, Julia Olkhovskaia, Tim van Erven
2025	J	`jnl`	Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions. CoRR Hidde Fokkema, Tim van Erven, Sara Magliacane
2024	J	`jnl`	An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems. CoRR Sarah Sachs, Hédi Hadiji, Tim van Erven, Mathias Staudigl
2024	A	`conf`	The Risks of Recourse in Binary Classification. AISTATS Hidde Fokkema, Damien Garreau, Tim van Erven
2023	A*	`conf`	Adaptive Selective Sampling for Online Prediction with Experts. NeurIPS Rui M. Castro, Fredrik Hellström, Tim van Erven
2023	J	`jnl`	Adaptive Selective Sampling for Online Prediction with Experts. CoRR Rui M. Castro, Fredrik Hellström, Tim van Erven
2023	J	`jnl`	Attribution-based Explanations that Provide Recourse Cannot be Robust. J. Mach. Learn. Res. Hidde Fokkema, Rianne de Heide, Tim van Erven
2023	A*	`conf`	First- and Second-Order Bounds for Adversarial Linear Contextual Bandits. NeurIPS Julia Olkhovskaya, Jack J. Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei
2023	J	`jnl`	First- and Second-Order Bounds for Adversarial Linear Contextual Bandits. CoRR Julia Olkhovskaya, Jack J. Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei
2023	A*	`conf`	Generalization Guarantees via Algorithm-dependent Rademacher Complexity. COLT Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli
2023	J	`jnl`	Generalization Guarantees via Algorithm-dependent Rademacher Complexity. CoRR Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli
2023	J	`jnl`	The Risks of Recourse in Binary Classification. CoRR Hidde Fokkema, Damien Garreau, Tim van Erven
2023	A*	`conf`	Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games. NeurIPS Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen
2023	J	`jnl`	Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games. CoRR Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen
2022	J	`jnl`	Attribution-based Explanations that Provide Recourse Cannot be Robust. CoRR Hidde Fokkema, Rianne de Heide, Tim van Erven
2022	A*	`conf`	Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. NeurIPS Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán
2022	J	`jnl`	Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. CoRR Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán
2022	B	`conf`	Distributed Online Learning for Joint Regret with Communication Constraints. ALT Dirk van der Hoeven, Hédi Hadiji, Tim van Erven
2022	J	`jnl`	Modifying Squint for Prediction with Expert Advice in a Changing Environment. CoRR Thom Neuteboom, Tim van Erven
2022	A*	`conf`	Scale-free Unconstrained Online Learning for Curved Losses. COLT Jack J. Mayo, Hédi Hadiji, Tim van Erven
2022	J	`jnl`	Scale-free Unconstrained Online Learning for Curved Losses. CoRR Jack J. Mayo, Hédi Hadiji, Tim van Erven
2021	J	`jnl`	Distributed Online Learning for Joint Regret with Communication Constraints. CoRR Dirk van der Hoeven, Hédi Hadiji, Tim van Erven
2021	J	`jnl`	MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. CoRR Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven
2021	J	`jnl`	MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. J. Mach. Learn. Res. Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven
2021	A*	`conf`	Robust Online Convex Optimization in the Presence of Outliers. COLT Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotlowski
2021	J	`jnl`	Robust Online Convex Optimization in the Presence of Outliers. CoRR Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotlowski
2020	J	`jnl`	Explaining Predictions by Approximating the Local Decision Boundary. CoRR Georgios Vlassopoulos, Tim van Erven, Henry Brighton, Vlado Menkovski
2020	A*	`conf`	Open Problem: Fast and Optimal Online Portfolio Selection. COLT Tim van Erven, Dirk van der Hoeven, Wojciech Kotlowski, Wouter M. Koolen
2019	A*	`conf`	Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. COLT Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven
2019	J	`jnl`	Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. CoRR Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven
2018	A*	`conf`	The Many Faces of Exponential Weights in Online Learning. COLT Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski
2018	J	`jnl`	The Many Faces of Exponential Weights in Online Learning. CoRR Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski
2016	—	`conf`	Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. NIPS Wouter M. Koolen, Peter Grünwald, Tim van Erven
2016	J	`jnl`	Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. CoRR Wouter M. Koolen, Peter Grünwald, Tim van Erven
2016	—	`conf`	MetaGrad: Multiple Learning Rates in Online Learning. NIPS Tim van Erven, Wouter M. Koolen
2016	J	`jnl`	MetaGrad: Multiple Learning Rates in Online Learning. CoRR Tim van Erven, Wouter M. Koolen
2015	J	`jnl`	Fast rates in statistical and online learning. CoRR Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson
2015	J	`jnl`	Fast rates in statistical and online learning. J. Mach. Learn. Res. Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson
2015	A*	`conf`	Second-order Quantile Methods for Experts and Combinatorial Games. COLT Wouter M. Koolen, Tim van Erven
2015	J	`jnl`	Second-order Quantile Methods for Experts and Combinatorial Games. CoRR Wouter M. Koolen, Tim van Erven
2014	J	`jnl`	A Second-order Bound with Excess Losses. CoRR Pierre Gaillard, Gilles Stoltz, Tim van Erven
2014	A*	`conf`	A second-order bound with excess losses. COLT Pierre Gaillard, Gilles Stoltz, Tim van Erven
2014	A*	`conf`	Follow the Leader with Dropout Perturbations. COLT Tim van Erven, Wojciech Kotlowski
2014	J	`jnl`	Follow the leader if you can, hedge if you must. J. Mach. Learn. Res. Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen
2014	—	`conf`	Learning the Learning Rate for Prediction with Expert Advice. NIPS Wouter M. Koolen, Tim van Erven, Peter Grünwald
2014	J	`jnl`	Rényi Divergence and Kullback-Leibler Divergence. IEEE Trans. Inf. Theory Tim van Erven, Peter Harremoës
2013	J	`jnl`	Follow the Leader If You Can, Hedge If You Must CoRR Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen
2012	—	`conf`	Mixability in Statistical Learning. NIPS Tim van Erven, Peter D. Grünwald, Mark D. Reid, Robert C. Williamson
2012	J	`jnl`	Mixability is Bayes Risk Curvature Relative to Log Loss. J. Mach. Learn. Res. Tim van Erven, Mark D. Reid, Robert C. Williamson
2012	J	`jnl`	Rényi Divergence and Kullback-Leibler Divergence CoRR Tim van Erven, Peter Harremoës
2011	—	`conf`	Adaptive Hedge. NIPS Tim van Erven, Peter Grunwald, Wouter M. Koolen, Steven de Rooij
2011	A*	`conf`	Mixability is Bayes Risk Curvature Relative to Log Loss. COLT Tim van Erven, Mark D. Reid, Robert C. Williamson
2010	J	`jnl`	Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors CoRR Wouter M. Koolen, Tim van Erven
2010	J	`jnl`	Rényi Divergence and Its Properties CoRR Tim van Erven, Peter Harremoës
2010	B	`conf`	Rényi divergence and majorization. ISIT Tim van Erven, Peter Harremoës
2010	J	`jnl`	Switching between Hidden Markov Models using Fixed Share CoRR Wouter M. Koolen, Tim van Erven
2009	A	`conf`	Learning the Switching Rate by Discretising Bernoulli Sources Online. AISTATS Steven de Rooij, Tim van Erven
2008	J	`jnl`	Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma CoRR Tim van Erven, Peter Grünwald, Steven de Rooij
2008	B	`conf`	The Catch-Up Phenomenon. ITW Peter Grunwald, Steven de Rooij, Tim van Erven
2007	—	`conf`	Catching Up Faster in Bayesian Model Selection and Model Averaging. NIPS Tim van Erven, Peter Grunwald, Steven de Rooij