Tim van Erven

According to our database, Tim van Erven authored at least 38 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems.

Sarah Sachs, Hédi Hadiji, Tim van Erven, Mathias Staudigl

CoRR, 2024

The Risks of Recourse in Binary Classification.

Hidde Fokkema, Damien Garreau, Tim van Erven

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Attribution-based Explanations that Provide Recourse Cannot be Robust.

Hidde Fokkema, Rianne de Heide, Tim van Erven

J. Mach. Learn. Res., 2023

Accelerated Rates between Stochastic and Adversarial Online Convex Optimization.

Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán

CoRR, 2023

First- and Second-Order Bounds for Adversarial Linear Contextual Bandits.

Julia Olkhovskaya, Jack J. Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games.

Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Selective Sampling for Online Prediction with Experts.

Rui M. Castro, Fredrik Hellström, Tim van Erven

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalization Guarantees via Algorithm-dependent Rademacher Complexity.

Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Modifying Squint for Prediction with Expert Advice in a Changing Environment.

Thom Neuteboom, Tim van Erven

CoRR, 2022

Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness.

Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scale-free Unconstrained Online Learning for Curved Losses.

Jack J. Mayo, Hédi Hadiji, Tim van Erven

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Distributed Online Learning for Joint Regret with Communication Constraints.

Dirk van der Hoeven, Hédi Hadiji, Tim van Erven

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

MetaGrad: Adaptation using Multiple Learning Rates in Online Learning.

Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven

J. Mach. Learn. Res., 2021

Robust Online Convex Optimization in the Presence of Outliers.

Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotlowski

Proceedings of the Conference on Learning Theory, 2021

2020

Explaining Predictions by Approximating the Local Decision Boundary.

Georgios Vlassopoulos, Tim van Erven, Henry Brighton, Vlado Menkovski

CoRR, 2020

Open Problem: Fast and Optimal Online Portfolio Selection.

Tim van Erven, Dirk van der Hoeven, Wojciech Kotlowski, Wouter M. Koolen

Proceedings of the Conference on Learning Theory, 2020

2019

Lipschitz Adaptivity with Multiple Learning Rates in Online Learning.

Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven

Proceedings of the Conference on Learning Theory, 2019

2018

The Many Faces of Exponential Weights in Online Learning.

Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski

Proceedings of the Conference On Learning Theory, 2018

2016

Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning.

Wouter M. Koolen, Peter Grünwald, Tim van Erven

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

MetaGrad: Multiple Learning Rates in Online Learning.

Tim van Erven, Wouter M. Koolen

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Fast rates in statistical and online learning.

Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson

J. Mach. Learn. Res., 2015

Second-order Quantile Methods for Experts and Combinatorial Games.

Wouter M. Koolen, Tim van Erven

Proceedings of The 28th Conference on Learning Theory, 2015

2014

Rényi Divergence and Kullback-Leibler Divergence.

Tim van Erven, Peter Harremoës

IEEE Trans. Inf. Theory, 2014

Follow the leader if you can, hedge if you must.

Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen

J. Mach. Learn. Res., 2014

Learning the Learning Rate for Prediction with Expert Advice.

Wouter M. Koolen, Tim van Erven, Peter Grünwald

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A second-order bound with excess losses.

Pierre Gaillard, Gilles Stoltz, Tim van Erven

Proceedings of The 27th Conference on Learning Theory, 2014

Follow the Leader with Dropout Perturbations.

Tim van Erven, Wojciech Kotlowski

Proceedings of The 27th Conference on Learning Theory, 2014

2012

Mixability is Bayes Risk Curvature Relative to Log Loss.

Tim van Erven, Mark D. Reid, Robert C. Williamson

J. Mach. Learn. Res., 2012

Mixability in Statistical Learning.

Tim van Erven, Peter D. Grünwald, Mark D. Reid, Robert C. Williamson

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Adaptive Hedge.

Tim van Erven, Peter Grunwald, Wouter M. Koolen, Steven de Rooij

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors

Wouter M. Koolen, Tim van Erven

CoRR, 2010

Switching between Hidden Markov Models using Fixed Share

Wouter M. Koolen, Tim van Erven

CoRR, 2010

Rényi Divergence and Its Properties

Tim van Erven, Peter Harremoës

CoRR, 2010

Rényi divergence and majorization.

Tim van Erven, Peter Harremoës

Proceedings of the IEEE International Symposium on Information Theory, 2010

2009

Learning the Switching Rate by Discretising Bernoulli Sources Online.

Steven de Rooij, Tim van Erven

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008

Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma

Tim van Erven, Peter Grünwald, Steven de Rooij

CoRR, 2008

The Catch-Up Phenomenon.

Peter Grunwald, Steven de Rooij, Tim van Erven

Proceedings of the 2008 IEEE Information Theory Workshop, 2008

2007

Catching Up Faster in Bayesian Model Selection and Model Averaging.

Tim van Erven, Peter Grunwald, Steven de Rooij

Proceedings of the Advances in Neural Information Processing Systems 20, 2007