conftrace_

Tim van Erven

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

Achievements

Jump to papers ↓
+8 more ↓ 🌍 Conference Polyglot (5) 🏃 Academic Marathon (13) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (15)
🐝 Cross-Pollinator (15) 🗺️ Taxonomy Completionist (31) 🏆 Keyword Champion (2) 🔬 Deep Specialist (12) 🔥 Unstoppable (7) 🗃️ Keyword Collector (80) 💎 Century Club (23) Prolific Year (5)

Conferences

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

Research topics

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 Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games NIPS 2023 First- and Second-Order Bounds for Adversarial Linear Contextual Bandits NIPS 2023 Adaptive Selective Sampling for Online Prediction with Experts NIPS 2023 Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023 Attribution-based Explanations that Provide Recourse Cannot be Robust JMLR 2023 Scale-free Unconstrained Online Learning for Curved Losses COLT 2022 Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness NIPS 2022 Distributed Online Learning for Joint Regret with Communication Constraints ALT 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 NIPS 2016 MetaGrad: Multiple Learning Rates in Online Learning NIPS 2016 Second-order Quantile Methods for Experts and Combinatorial Games COLT 2015 Fast Rates in Statistical and Online Learning JMLR 2015 Follow the Leader If You Can, Hedge If You Must JMLR 2014 A second-order bound with excess losses COLT 2014 Learning the Learning Rate for Prediction with Expert Advice NIPS 2014 Follow the Leader with Dropout Perturbations COLT 2014 Mixability is Bayes Risk Curvature Relative to Log Loss JMLR 2012