Tim van Erven
24 papers · 2012–2026 · 5 conferences · across top CS/AI conferences
Achievements
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🌍 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)
Top co-authors
Research topics
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
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