Nadav Hallak

5 papers · 2020–2025 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (13)

Venues

ICML (3) ICLR (1) NeurIPS (1)

Top co-authors

Volkan Cevher (3) Panayotis Mertikopoulos (2) Elazar Gershuni (1) Ran Moshe (1) Fiana Raiber (1) Ali Kavis (1) Paul Rolland (1) Dan Greenstein (1) Oren Somekh (1) Yaroslav Fyodorov (1)

Research topics

Machine Learning (5) Optimization & Theory · Machine Learning (5) Mathematics & Optimization (3) Optimization (3) Artificial Intelligence (2) Core AI (2) Deep Learning (1) Learning Types (1) Optimization & Theory · Deep Learning (1)

Keywords

stochastic optimization (3) non-convex optimization (2) adversarial robustness (1) neural network training (1) online learning (1) transfer learning (1) convex optimization (1) neural network optimization (1) constrained optimization (1) regret minimization (1) mirror descent (1) subset selection (1) conditional gradient (1) proximal operator (1) convergence guarantee (1) projected gradient (1) lipschitz constant (1) black-box setting (1) relative error (1) saddle point (1)

Papers

A Stochastic Approach to the Subset Selection Problem via Mirror Descent ICLR 2025 A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle ICML 2024 Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach ICML 2021 Efficient Proximal Mapping of the 1-path-norm of Shallow Networks ICML 2020 On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems NeurIPS 2020