Roi Livni
36 papers · 2012–2026 · 6 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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πΊοΈ Taxonomy Completionist (50) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Deep Specialist
(18)
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(12)
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(3)
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Keyword Champion
(8)
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Keyword Pioneer
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Unstoppable Β· Bronze
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Trend Setter
β
The Questioner
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Keyword Collector
(144)
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Conference Pioneer
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Century Club Β· Bronze
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Prolific Year Β· Productive
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Research topics
Machine Learning
(33)
Optimization & Theory Β· Machine Learning
(29)
Mathematics & Optimization
(17)
Optimization
(14)
Core Methods
(10)
Learning Types
(9)
Deep Learning
(6)
Artificial Intelligence
(4)
Application Areas
(4)
Mathematics
(4)
Computer Science
(3)
Core AI
(3)
Foundations
(3)
Optimization & Theory Β· Deep Learning
(3)
Models
(2)
Keywords
regret bound
(9)
sample complexity
(9)
stochastic convex optimization
(8)
online learning
(8)
learning theory
(6)
stochastic gradient descent
(5)
generalization bound
(5)
kernel methods
(4)
uniform convergence
(3)
differential privacy
(3)
low-rank matrix
(3)
switching cost
(3)
vc dimension
(3)
multi-armed bandit
(3)
gradient descent
(3)
generalization error
(3)
support vector machine
(2)
learning rate
(2)
linear classification
(2)
concept class
(2)
Papers
CARLoS: Retrieval via Concise Assessment Representation of LoRAs at Scale
CVPR 2026
Learning from Equivalence Queries, Revisited
COLT 2026
Margin in Abstract Spaces
COLT 2026
Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
ICML 2025
Credit Attribution and Stable Compression
NeurIPS 2024
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing
ICML 2024
The sample complexity of ERMs in stochastic convex optimization
AISTATS 2024
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
NeurIPS 2024
Information Theoretic Lower Bounds for Information Theoretic Upper Bounds
NeurIPS 2023
Benign Underfitting of Stochastic Gradient Descent
NeurIPS 2022
Better Best of Both Worlds Bounds for Bandits with Switching Costs
NeurIPS 2022
Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization
NeurIPS 2022
Littlestone Classes are Privately Online Learnable
NeurIPS 2021
Never Go Full Batch (in Stochastic Convex Optimization)
NeurIPS 2021
Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games
COLT 2021
SGD Generalizes Better Than GD (And Regularization Doesnβt Help)
COLT 2021
A Limitation of the PAC-Bayes Framework
NeurIPS 2020
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study
NeurIPS 2020
Prediction with Corrupted Expert Advice
NeurIPS 2020
Synthetic Data Generators -- Sequential and Private
NeurIPS 2020
Generalize Across Tasks: Efficient Algorithms for Linear
Representation Learning
ALT 2019
Graph-based Discriminators: Sample Complexity and Expressiveness
NeurIPS 2019
On Communication Complexity of Classification Problems
COLT 2019
Affine-Invariant Online Optimization and the Low-rank Experts Problem
NeurIPS 2017
Bandits with Movement Costs and Adaptive Pricing
COLT 2017
Effective Semisupervised Learning on Manifolds
COLT 2017
Learning Infinite Layer Networks Without the Kernel Trick
ICML 2017
Multi-Armed Bandits with Metric Movement Costs
NeurIPS 2017
Improper Deep Kernels
AISTATS 2016
Online Learning with Low Rank Experts
COLT 2016
Online Pricing with Strategic and Patient Buyers
NeurIPS 2016
Classification with Low Rank and Missing Data
ICML 2015
On the Computational Efficiency of Training Neural Networks
NeurIPS 2014
Honest Compressions and Their Application to Compression Schemes
COLT 2013
Vanishing Component Analysis
ICML 2013
A Simple Geometric Interpretation of SVM using Stochastic Adversaries
AISTATS 2012