Stephen Wright
23 papers · 2011–2024 · 4 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (11) π Conference Polyglot (4)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Interdisciplinary Bridge
π¬
Deep Specialist
(12)
π
Keyword Champion
π
Triple Crown
ποΈ
Keyword Collector
(93)
β‘
Prolific Year
(6)
π
Trend Setter
π
Century Club
(23)
Conferences
ICML (11)
NIPS (9)
AISTATS (2)
ICLR (1)
Top co-authors
Keywords
convex optimization
(4)
stochastic gradient
(3)
first-order method
(3)
nonconvex optimization
(2)
gradient descent
(2)
convergence rate
(2)
sparse optimization
(2)
variance reduction
(2)
bilevel optimization
(2)
online learning
(2)
coordinate descent
(2)
model calibration
(1)
metric learning
(1)
sample complexity
(1)
hyperparameter optimization
(1)
stochastic gradient descent
(1)
stochastic optimization
(1)
markov chain monte carlo
(1)
finite-sum optimization
(1)
continual learning
(1)
Papers
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
ICML 2024
On the Complexity of Teaching a Family of Linear Behavior Cloning Learners
NIPS 2024
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
ICLR 2024
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
ICML 2024
Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning
ICML 2024
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
ICML 2024
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
ICML 2023
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
NIPS 2023
A Fully First-Order Method for Stochastic Bilevel Optimization
ICML 2023
Cut your Losses with Squentropy
ICML 2023
Coordinate Linear Variance Reduction for Generalized Linear Programming
NIPS 2022
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach
NIPS 2022
Random Coordinate Underdamped Langevin Monte Carlo
AISTATS 2021
Blended Conditonal Gradients
ICML 2019
Bilinear Bandits with Low-rank Structure
ICML 2019
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
ICML 2019
ATOMO: Communication-efficient Learning via Atomic Sparsification
NIPS 2018
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
ICML 2018
Improved Strongly Adaptive Online Learning using Coin Betting
AISTATS 2017
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms
NIPS 2017
Beyond the Birkhoff Polytope: Convex Relaxations for Vector Permutation Problems
NIPS 2014
An Approximate, Efficient LP Solver for LP Rounding
NIPS 2013
Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
NIPS 2011