Tim van Erven

24 papers · 2012–2026 · 5 venues · across top CS/AI venues

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Achievements

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🗺️ Taxonomy Completionist (33) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🔬 Deep Specialist (13) 🏆 Keyword Champion (4) 📈 Trend Setter 🔥 Unstoppable · Bronze ⚡ Prolific Year · Productive 💎 Century Club · Bronze 🗃️ Keyword Collector (95)

Venues

COLT (8) NeurIPS (7) JMLR (5) ALT (3) AISTATS (1)

Top co-authors

Wouter M. Koolen (8) Hedi Hadiji (5) Sarah Sachs (5) Dirk van der Hoeven (4) Hidde Fokkema (2) Robert C. Williamson (2) Mark D. Reid (2) Peter Grünwald (2) Peter D. Grünwald (2) Wojciech Kotłowski (2)

Research topics

Machine Learning (23) Optimization & Theory (22) Mathematics & Optimization (18) Optimization (15) Learning Types (14) Application Areas (4) Artificial Intelligence (3) Core AI (3) Mathematics (2) Bayesian & Probabilistic (1) Core Methods (1) Statistics (1)

Keywords

regret bound (12) online learning (12) online convex optimization (7) learning rate (5) expert advice (4) adversarial learning (3) stochastic optimization (3) learning theory (3) second-order bound (2) prediction with expert advice (2) fast rate (2) game theory (2) exponential weight (2) bernstein condition (2) adaptive method (2) adaptive learning rate (2) exp-concave function (2) hedge algorithm (1) feature importance (1) risk management (1)

Papers

Nearly Minimax Discrete Distribution Estimation in Kullback-Leibler Divergence with High Probability ALT 2026 An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems. ALT 2025 The Risks of Recourse in Binary Classification AISTATS 2024 Adaptive Selective Sampling for Online Prediction with Experts NeurIPS 2023 Attribution-based Explanations that Provide Recourse Cannot be Robust JMLR 2023 First- and Second-Order Bounds for Adversarial Linear Contextual Bandits NeurIPS 2023 Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023 Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games NeurIPS 2023 Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness NeurIPS 2022 Distributed Online Learning for Joint Regret with Communication Constraints ALT 2022 Scale-free Unconstrained Online Learning for Curved Losses COLT 2022 MetaGrad: Adaptation using Multiple Learning Rates in Online Learning JMLR 2021 Robust Online Convex Optimization in the Presence of Outliers COLT 2021 Open Problem: Fast and Optimal Online Portfolio Selection COLT 2020 Lipschitz Adaptivity with Multiple Learning Rates in Online Learning COLT 2019 Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning NeurIPS 2016 MetaGrad: Multiple Learning Rates in Online Learning NeurIPS 2016 Fast Rates in Statistical and Online Learning JMLR 2015 Second-order Quantile Methods for Experts and Combinatorial Games COLT 2015 A second-order bound with excess losses COLT 2014 Follow the Leader If You Can, Hedge If You Must JMLR 2014 Follow the Leader with Dropout Perturbations COLT 2014 Learning the Learning Rate for Prediction with Expert Advice NeurIPS 2014 Mixability is Bayes Risk Curvature Relative to Log Loss JMLR 2012