← Authors

Shai Shalev-shwartz

58 papers · 2005–2025 · 8 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (20) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (24) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (8) 🐝 Cross-Pollinator (15) 🌟 Keyword Trendsetter Combo (3) 🌱 Topic Pioneer πŸ‘₯ Mega-Team (61) πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (4) πŸ—ƒοΈ Keyword Collector (111) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner πŸ’Ž Century Club (58) πŸ”₯ Unstoppable (13)

Conferences

JMLR (18) NIPS (14) ICML (11) COLT (8) ICLR (4) ACL (1) AISTATS (1) ALT (1)

Top co-authors

Amit Daniely (9) Ohad Shamir (8) Eran Malach (7) Alon Gonen (7) Sivan Sabato (6) Yoram Singer (6) Tong Zhang (4) Elad Hazan (3) Yonatan Wexler (3) Amir Globerson (3)

Keywords

online learning (8) convex optimization (8) sample complexity (7) empirical risk minimization (7) stochastic optimization (6) multiclass classification (6) gradient descent (5) stochastic gradient descent (5) support vector machine (4) computational complexity (4) learning theory (4) feature selection (4) non-convex optimization (4) active learning (3) boosting algorithm (3) halfspace learning (3) matrix completion (3) collaborative filtering (3) stochastic dual coordinate ascent (3) regularized loss minimization (3)

Papers

Jamba: Hybrid Transformer-Mamba Language Models ICLR 2025
Knowledge Distillation: Bad Models Can Be Good Role Models NIPS 2022
When Hardness of Approximation Meets Hardness of Learning JMLR 2022
Computational Separation Between Convolutional and Fully-Connected Networks ICLR 2021
SenseBERT: Driving Some Sense into BERT ACL 2020
The Implications of Local Correlation on Learning Some Deep Functions NIPS 2020
Distribution Free Learning with Local Queries ALT 2020
The Implicit Bias of Depth: How Incremental Learning Drives Generalization ICLR 2020
Is Deeper Better only when Shallow is Good? NIPS 2019
Average Stability is Invariant to Data Preconditioning. Implications to Exp-concave Empirical Risk Minimization JMLR 2018
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data ICLR 2018
Effective Semisupervised Learning on Manifolds COLT 2017
Fast Rates for Empirical Risk Minimization of Strict Saddle Problems COLT 2017
Decoupling "when to update" from "how to update" NIPS 2017
Failures of Gradient-Based Deep Learning ICML 2017
On Graduated Optimization for Stochastic Non-Convex Problems ICML 2016
Learning a Metric Embedding for Face Recognition using the Multibatch Method NIPS 2016
On Lower and Upper Bounds in Smooth and Strongly Convex Optimization JMLR 2016
Subspace Learning with Partial Information JMLR 2016
Solving Ridge Regression using Sketched Preconditioned SVRG ICML 2016
Minimizing the Maximal Loss: How and Why ICML 2016
SDCA without Duality, Regularization, and Individual Convexity ICML 2016
Complexity Theoretic Limitations on Learning DNF’s COLT 2016
Strongly Adaptive Online Learning ICML 2015
Beyond Convexity: Stochastic Quasi-Convex Optimization NIPS 2015
Learning Sparse Low-Threshold Linear Classifiers JMLR 2015
Multiclass Learnability and the ERM Principle JMLR 2015
On the Computational Efficiency of Training Neural Networks NIPS 2014
The Complexity of Learning Halfspaces using Generalized Linear Methods COLT 2014
Optimal learners for multiclass problems COLT 2014
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization ICML 2014
K-means recovers ICA filters when independent components are sparse ICML 2014
Matrix Completion with the Trace Norm: Learning, Bounding, and Transducing JMLR 2014
Efficient Active Learning of Halfspaces: an Aggressive Approach ICML 2013
Accelerated Mini-Batch Stochastic Dual Coordinate Ascent NIPS 2013
More data speeds up training time in learning halfspaces over sparse vectors NIPS 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization JMLR 2013
Learning Optimally Sparse Support Vector Machines ICML 2013
Efficient Active Learning of Halfspaces: An Aggressive Approach JMLR 2013
Vanishing Component Analysis ICML 2013
Regularization Techniques for Learning with Matrices JMLR 2012
Using More Data to Speed-up Training Time AISTATS 2012
Near-Optimal Algorithms for Online Matrix Prediction COLT 2012
Multiclass Learnability and the ERM principle COLT 2011
Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing COLT 2011
Stochastic Methods for -regularized Loss Minimization JMLR 2011
Efficient Learning with Partially Observed Attributes JMLR 2011
ShareBoost: Efficient multiclass learning with feature sharing NIPS 2011
Learnability, Stability and Uniform Convergence JMLR 2010
Mind the Duality Gap: Logarithmic regret algorithms for online optimization NIPS 2008
Ranking Categorical Features Using Generalization Properties JMLR 2008
Online Learning of Complex Prediction Problems Using Simultaneous Projections JMLR 2008
Fast Rates for Regularized Objectives NIPS 2008
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra JMLR 2006
Online Passive-Aggressive Algorithms JMLR 2006
Online Classification for Complex Problems Using Simultaneous Projections NIPS 2006
Convex Repeated Games and Fenchel Duality NIPS 2006
Smooth Ξ΅-Insensitive Regression by Loss Symmetrization JMLR 2005