← Authors

Satyen Kale

57 papers · 2007–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (8) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (22) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (3) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (18) 🏠 Conference Loyalist (20) 🌟 Keyword Trendsetter Combo (4) 🀝 Dynamic Duo (12) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (83) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (17) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ’Ž Century Club (57)

Conferences

NIPS (20) COLT (12) ICML (11) ALT (4) AISTATS (3) JMLR (3) ICLR (2) IJCAI (2)

Top co-authors

Elad Hazan (12) Sanjiv Kumar (8) Mehryar Mohri (7) Haipeng Luo (5) Karthik Sridharan (5) Sashank Reddi (5) Naman Agarwal (5) Sashank J. Reddi (4) Pranjal Awasthi (4) Stefani Karp (3)

Keywords

online learning (20) regret bound (15) stochastic optimization (6) regret minimization (6) multi-armed bandit (5) stochastic gradient descent (4) differential privacy (4) multiclass classification (3) online algorithm (3) sample complexity (3) federated learning (3) adversarial setting (3) convex optimization (3) convergence analysis (3) online convex optimization (3) wasserstein distance (2) gradient boosting (2) learning theory (2) distributed optimization (2) nonconvex optimization (2)

Papers

Efficient stagewise pretraining via progressive subnetworks ICLR 2025
Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data ALT 2024
Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements ICML 2024
Beyond Uniform Lipschitz Condition in Differentially Private Optimization ICML 2023
On the Convergence of Federated Averaging with Cyclic Client Participation ICML 2023
Differentially Private and Lazy Online Convex Optimization COLT 2023
Efficient Training of Language Models using Few-Shot Learning ICML 2023
Self-Consistency of the Fokker Planck Equation COLT 2022
Reproducibility in Optimization: Theoretical Framework and Limits NIPS 2022
Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States COLT 2022
Agnostic Learnability of Halfspaces via Logistic Loss ICML 2022
Private Matrix Approximation and Geometry of Unitary Orbits COLT 2022
Efficient Methods for Online Multiclass Logistic Regression ALT 2022
Federated Functional Gradient Boosting AISTATS 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent NIPS 2022
Breaking the centralized barrier for cross-device federated learning NIPS 2021
Learning with User-Level Privacy NIPS 2021
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs NIPS 2021
A Deep Conditioning Treatment of Neural Networks ALT 2021
PAC-Bayes Learning Bounds for Sample-Dependent Priors NIPS 2020
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020
Estimating Training Data Influence by Tracing Gradient Descent NIPS 2020
Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces NIPS 2019
Algorithmic Learning Theory 2019: Preface ALT 2019
Hypothesis Set Stability and Generalization NIPS 2019
Escaping Saddle Points with Adaptive Gradient Methods ICML 2019
Stochastic Negative Mining for Learning with Large Output Spaces AISTATS 2019
Online Learning of Quantum States NIPS 2018
Adaptive Methods for Nonconvex Optimization NIPS 2018
On the Convergence of Adam and Beyond ICLR 2018
Loss Decomposition for Fast Learning in Large Output Spaces ICML 2018
Logistic Regression: The Importance of Being Improper COLT 2018
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP ICML 2017
Parameter-Free Online Learning via Model Selection NIPS 2017
Preface: Conference on Learning Theory (COLT), 2017 COLT 2017
Hardness of Online Sleeping Combinatorial Optimization Problems NIPS 2016
Online Sparse Linear Regression COLT 2016
Optimal and Adaptive Algorithms for Online Boosting IJCAI 2016
Optimal and Adaptive Algorithms for Online Boosting ICML 2015
Online Gradient Boosting NIPS 2015
Open Problem: Efficient Online Sparse Regression COLT 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits ICML 2014
Beyond the Regret Minimization Barrier: Optimal Algorithms for Stochastic Strongly-Convex Optimization JMLR 2014
Multiarmed Bandits With Limited Expert Advice COLT 2014
Bargaining for Revenue Shares on Tree Trading Networks IJCAI 2013
Adaptive Market Making via Online Learning NIPS 2013
Online Submodular Minimization JMLR 2012
Near-Optimal Algorithms for Online Matrix Prediction COLT 2012
Contextual Bandit Learning with Predictable Rewards AISTATS 2012
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization COLT 2011
Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction NIPS 2011
Better Algorithms for Benign Bandits JMLR 2011
A simple multi-armed bandit algorithm with optimal variation-bounded regret COLT 2011
Non-Stochastic Bandit Slate Problems NIPS 2010
On Stochastic and Worst-case Models for Investing NIPS 2009
Beyond Convexity: Online Submodular Minimization NIPS 2009
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria NIPS 2007