← Authors

Roi Livni

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

Achievements

🌍 Conference Polyglot (5) 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (11) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (13) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🀝 Dynamic Duo (12) πŸ”¬ Deep Specialist (16) πŸ† Keyword Champion πŸ”₯ Unstoppable (7) πŸš€ Conference Pioneer ⚑ Prolific Year (5) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (120) πŸ’Ž Century Club (33) πŸ“ˆ Trend Setter

Conferences

NIPS (17) COLT (7) ICML (5) AISTATS (3) ALT (1)

Top co-authors

Tomer Koren (12) Yishay Mansour (8) Amir Globerson (5) Shay Moran (5) Idan Amir (5) Shai Shalev-shwartz (3) Elad Hazan (3) Amir Yehudayoff (2) Daniel Carmon (2) Idan Attias (2)

Research topics

Differential Privacy (1) Privacy (1)

Keywords

sample complexity (9) regret bound (8) online learning (8) learning theory (6) stochastic convex optimization (6) stochastic gradient descent (4) generalization bound (4) multi-armed bandit (3) vc dimension (3) kernel methods (3) generalization error (3) differential privacy (3) uniform convergence (3) switching cost (3) gradient descent (3) learning rate (2) pac learning (2) low-rank matrix (2) expert advice (2) stochastic optimization (2)

Papers

Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization ICML 2025
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization NIPS 2024
Credit Attribution and Stable Compression NIPS 2024
The sample complexity of ERMs in stochastic convex optimization AISTATS 2024
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing ICML 2024
Information Theoretic Lower Bounds for Information Theoretic Upper Bounds NIPS 2023
Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization NIPS 2022
Better Best of Both Worlds Bounds for Bandits with Switching Costs NIPS 2022
Benign Underfitting of Stochastic Gradient Descent NIPS 2022
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021
Littlestone Classes are Privately Online Learnable NIPS 2021
Never Go Full Batch (in Stochastic Convex Optimization) NIPS 2021
SGD Generalizes Better Than GD (And Regularization Doesn’t Help) COLT 2021
Prediction with Corrupted Expert Advice NIPS 2020
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study NIPS 2020
Synthetic Data Generators -- Sequential and Private NIPS 2020
A Limitation of the PAC-Bayes Framework NIPS 2020
Graph-based Discriminators: Sample Complexity and Expressiveness NIPS 2019
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning ALT 2019
On Communication Complexity of Classification Problems COLT 2019
Learning Infinite Layer Networks Without the Kernel Trick ICML 2017
Affine-Invariant Online Optimization and the Low-rank Experts Problem NIPS 2017
Multi-Armed Bandits with Metric Movement Costs NIPS 2017
Effective Semisupervised Learning on Manifolds COLT 2017
Bandits with Movement Costs and Adaptive Pricing COLT 2017
Online Pricing with Strategic and Patient Buyers NIPS 2016
Online Learning with Low Rank Experts COLT 2016
Improper Deep Kernels AISTATS 2016
Classification with Low Rank and Missing Data ICML 2015
On the Computational Efficiency of Training Neural Networks NIPS 2014
Vanishing Component Analysis ICML 2013
Honest Compressions and Their Application to Compression Schemes COLT 2013
A Simple Geometric Interpretation of SVM using Stochastic Adversaries AISTATS 2012