← Authors

Amit Daniely

36 papers · 2011–2025 · 7 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (11) πŸ—ΊοΈ Taxonomy Completionist (30) 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (14) πŸŒ‰ Interdisciplinary Bridge 🐺 Lone Wolf (5) πŸ”¬ Deep Specialist (25) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (118) ⚑ Prolific Year (7) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (36) πŸ”₯ Unstoppable (7) ❓ The Questioner

Conferences

NIPS (14) COLT (12) ALT (4) AISTATS (2) ICLR (2) ICML (1) JMLR (1)

Top co-authors

Shai Shalev-shwartz (9) Gal Vardi (4) Sivan Sabato (3) Yishay Mansour (3) Elad Granot (3) Mariano Schain (3) Nati Srebro (2) Shai Ben-David (2) Alon Cohen (2) Gilad Yehudai (2)

Keywords

sample complexity (9) neural network (9) learning theory (8) multiclass classification (6) pac learning (6) online learning (3) computational complexity (3) kernel methods (3) empirical risk minimization (3) hypothesis class (3) agnostic learning (3) hardness result (3) gradient descent (3) distributed learning (2) generalization bound (2) representation learning (2) approximation algorithm (2) stochastic gradient descent (2) convex optimization (2) halfspace learning (2)

Papers

Locally Optimal Descent for Dynamic Stepsize Scheduling AISTATS 2025
Existence of Adversarial Examples for Random Convolutional Networks via Isoperimetric Inequalities on $\mathbb{SO}(d)$ COLT 2025
RedEx: Beyond Fixed Representation Methods via Convex Optimization ALT 2024
On the Sample Complexity of Two-Layer Networks: Lipschitz Vs. Element-Wise Lipschitz Activation ALT 2024
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria NIPS 2023
Most Neural Networks Are Almost Learnable NIPS 2023
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy NIPS 2023
An Exact Poly-Time Membership-Queries Algorithm for Extracting a Three-Layer ReLU Network ICLR 2023
Monotone Learning COLT 2022
Asynchronous Stochastic Optimization Robust to Arbitrary Delays NIPS 2021
From Local Pseudorandom Generators to Hardness of Learning COLT 2021
Distribution Free Learning with Local Queries ALT 2020
The Implicit Bias of Depth: How Incremental Learning Drives Generalization ICLR 2020
Hardness of Learning Neural Networks with Natural Weights NIPS 2020
Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations NIPS 2020
Neural Networks Learning and Memorization with (almost) no Over-Parameterization NIPS 2020
Learning Parities with Neural Networks NIPS 2020
ID3 Learns Juntas for Smoothed Product Distributions COLT 2020
Open Problem: Is Margin Sufficient for Non-Interactive Private Distributed Learning? COLT 2019
Generalization Bounds for Neural Networks via Approximate Description Length NIPS 2019
Locally Private Learning without Interaction Requires Separation NIPS 2019
Learning Rules-First Classifiers AISTATS 2019
Competitive ratio vs regret minimization: achieving the best of both worlds ALT 2019
SGD Learns the Conjugate Kernel Class of the Network NIPS 2017
Depth Separation for Neural Networks COLT 2017
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NIPS 2016
Complexity Theoretic Limitations on Learning DNF’s COLT 2016
Multiclass Learnability and the ERM Principle JMLR 2015
A PTAS for Agnostically Learning Halfspaces COLT 2015
Strongly Adaptive Online Learning ICML 2015
The Complexity of Learning Halfspaces using Generalized Linear Methods COLT 2014
Optimal learners for multiclass problems COLT 2014
The price of bandit information in multiclass online classification COLT 2013
More data speeds up training time in learning halfspaces over sparse vectors NIPS 2013
Multiclass Learning Approaches: A Theoretical Comparison with Implications NIPS 2012
Multiclass Learnability and the ERM principle COLT 2011