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07/31/2023
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
Coordinate descent methods are popular in machine learning and optimizat...
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07/13/2023
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
We study the problem of learning general (i.e., not necessarily homogene...
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06/28/2023
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise
We study the problem of PAC learning γ-margin halfspaces with Random Cla...
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06/21/2023
Empirical Risk Minimization with Shuffled SGD: A Primal-Dual Perspective and Improved Bounds
Stochastic gradient descent (SGD) is perhaps the most prevalent optimiza...
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06/13/2023
Robustly Learning a Single Neuron via Sharpness
We study the problem of learning a single neuron with respect to the L_2...
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03/28/2023
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
Exploiting partial first-order information in a cyclic way is arguably t...
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12/09/2022
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
Nonconvex optimization is central in solving many machine learning probl...
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03/17/2022
A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems
We study stochastic monotone inclusion problems, which widely appear in ...
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03/08/2022
A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data
Nonnegative (linear) least square problems are a fundamental class of pr...
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11/02/2021
Coordinate Linear Variance Reduction for Generalized Linear Programming
We study a class of generalized linear programs (GLP) in a large-scale s...
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02/26/2021
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
We study structured nonsmooth convex finite-sum optimization that appear...
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02/26/2021
Fast Cyclic Coordinate Dual Averaging with Extrapolation for Generalized Variational Inequalities
We propose the Cyclic cOordinate Dual avEraging with extRapolation (CODE...
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02/12/2021
Parameter-free Locally Accelerated Conditional Gradients
Projection-free conditional gradient (CG) methods are the algorithms of ...
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01/28/2021
Potential Function-based Framework for Making the Gradients Small in Convex and Min-Max Optimization
Making the gradients small is a fundamental optimization problem that ha...
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01/26/2021
Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems
Composite minimization is a powerful framework in large-scale convex opt...
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10/31/2020
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
The use of min-max optimization in adversarial training of deep neural n...
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02/20/2020
Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities
We leverage the connections between nonexpansive maps, monotone Lipschit...
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06/29/2019
Conjugate Gradients and Accelerated Methods Unified: The Approximate Duality Gap View
This note provides a novel, simple analysis of the method of conjugate g...
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06/19/2019
Locally Accelerated Conditional Gradients
Conditional gradient methods form a class of projection-free first-order...
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06/02/2019
Generalized Momentum-Based Methods: A Hamiltonian Perspective
We take a Hamiltonian-based perspective to generalize Nesterov's acceler...
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05/30/2019
Langevin Monte Carlo without Smoothness
Langevin Monte Carlo (LMC) is an iterative algorithm used to generate sa...
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01/19/2019
A Hierarchical WDM-based Scalable Data Center Network Architecture
Massive data centers are at the heart of the Internet. The rapid growth ...
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11/05/2018
Lower Bounds for Parallel and Randomized Convex Optimization
We study the question of whether parallelization in the exploration of t...
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08/07/2018
Width-Independence Beyond Linear Objectives: Distributed Fair Packing and Covering Algorithms
In network routing and resource allocation, α-fair utility functions are...
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05/31/2018
On Acceleration with Noise-Corrupted Gradients
Accelerated algorithms have broad applications in large-scale optimizati...
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01/03/2018
Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks
Full-duplex (FD) wireless is an attractive communication paradigm with h...
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06/14/2017