Roi Livni
33 papers · 2012–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (5) π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (12) π Interdisciplinary Bridge π Academic Marathon (13)
π
Academic Marathon
(13)
πΊοΈ
Taxonomy Completionist
(12)
π§
Keyword Pioneer
π€
Dynamic Duo
(12)
π¬
Deep Specialist
(16)
π
Keyword Champion
π₯
Unstoppable
(7)
π
Conference Pioneer
β‘
Prolific Year
(5)
β
The Questioner
ποΈ
Keyword Collector
(120)
π
Century Club
(33)
π
Trend Setter
Conferences
NIPS (17)
COLT (7)
ICML (5)
AISTATS (3)
ALT (1)
Top co-authors
Research topics
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 Doesnβt 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