Tim van Erven

23 papers · 2012–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) 🏃 Academic Marathon (13) 🐝 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 (2) AISTATS (1)

Top co-authors

Wouter M. Koolen (8) Hedi Hadiji (5) Sarah Sachs (5) Dirk van der Hoeven (3) Hidde Fokkema (2) Robert C. Williamson (2) Mark D. Reid (2) Peter Grünwald (2) Peter D. Grünwald (2) Wojciech Kotłowski (2)

Keywords

regret bound (10) online learning (9) online convex optimization (7) learning rate (5) expert advice (4) adversarial learning (3) stochastic optimization (3) learning theory (3) bernstein condition (2) exp-concave function (2) adaptive method (2) fast rate (2) game theory (2) second-order bound (2) outlier detection (1) hedge algorithm (1) feature importance (1) sequential decision making (1) risk management (1) stochastic gradient (1)

Papers

An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems. ALT 2025

The Risks of Recourse in Binary Classification AISTATS 2024

Generalization Guarantees via Algorithm-dependent Rademacher Complexity COLT 2023

Adaptive Selective Sampling for Online Prediction with Experts NIPS 2023

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

Attribution-based Explanations that Provide Recourse Cannot be Robust JMLR 2023

Distributed Online Learning for Joint Regret with Communication Constraints ALT 2022

Scale-free Unconstrained Online Learning for Curved Losses COLT 2022

Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness NIPS 2022

Robust Online Convex Optimization in the Presence of Outliers COLT 2021

MetaGrad: Adaptation using Multiple Learning Rates in Online Learning JMLR 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 with Dropout Perturbations COLT 2014

A second-order bound with excess losses COLT 2014

Learning the Learning Rate for Prediction with Expert Advice NIPS 2014

Follow the Leader If You Can, Hedge If You Must JMLR 2014

Mixability is Bayes Risk Curvature Relative to Log Loss JMLR 2012