Idan Attias

17 papers · 2019–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (14) 🗺️ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🏃 Academic Marathon (6) 🐣 Hot Topic Early Bird 🏆 Keyword Champion (2) 🔬 Deep Specialist (10) 🗃️ Keyword Collector (54) 💎 Century Club (17) ⚡ Prolific Year (6)

Conferences

ICML (5) NIPS (4) COLT (3) ALT (2) JMLR (2) AAAI (1)

Top co-authors

Steve Hanneke (6) Yishay Mansour (5) Aryeh Kontorovich (4) Daniel M. Roy (4) Amin Karbasi (2) Grigoris Velegkas (2) Ziyi Liu (2) Alkis Kalavasis (2) Roi Livni (2) Maxwell K. Fishelson (1)

Keywords

online learning (4) pac learning (3) adversarial robustness (3) sample complexity (3) generalization bound (3) binary classification (2) fat-shattering dimension (2) regret bound (2) zero-sum game (2) multi-class classification (1) empirical risk minimization (1) minimax optimization (1) adversarial learning (1) rademacher complexity (1) expert advice (1) online mirror descent (1) robust classification (1) regression analysis (1) sample compression (1) game theory (1)

Papers

PAC Learning with Improvements ICML 2025

Sample Compression Scheme Reductions ALT 2025

Capacity-Constrained Online Learning with Delays: Scheduling Frameworks and Regret Trade-offs COLT 2025

Fat-Shattering Dimension of k-fold Aggregations JMLR 2024

Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood NIPS 2024

Universal Rates for Regression: Separations between Cut-Off and Absolute Loss COLT 2024

Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing ICML 2024

Agnostic Sample Compression Schemes for Regression ICML 2024

Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals ICML 2024

Online Learning and Solving Infinite Games with an ERM Oracle COLT 2023

Adversarially Robust PAC Learnability of Real-Valued Functions ICML 2023

Optimal Learners for Realizable Regression: PAC Learning and Online Learning NIPS 2023

Learning Revenue Maximization Using Posted Prices for Stochastic Strategic Patient Buyers AAAI 2023

A Characterization of Semi-Supervised Adversarially Robust PAC Learnability NIPS 2022

Improved Generalization Bounds for Adversarially Robust Learning JMLR 2022

Prediction with Corrupted Expert Advice NIPS 2020

Improved Generalization Bounds for Robust Learning ALT 2019