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06/23/2023
On a Class of Gibbs Sampling over Networks
We consider the sampling problem from a composite distribution whose pot...
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05/26/2023
Mitigating Catastrophic Forgetting in Long Short-Term Memory Networks
Continual learning on sequential data is critical for many machine learn...
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02/15/2023
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
Quasar convexity is a condition that allows some first-order methods to ...
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11/02/2022
Convergence in KL Divergence of the Inexact Langevin Algorithm with Application to Score-based Generative Models
We study the Inexact Langevin Algorithm (ILA) for sampling using estimat...
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10/28/2022
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings
Distributed machine learning (DML) can be an important capability for mo...
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10/18/2022
Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation
We consider a setting that a model needs to adapt to a new domain under ...
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07/05/2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time
Hamiltonian Monte Carlo (HMC) is a popular method in sampling. While the...
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06/22/2022
Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out
Heavy Ball (HB) nowadays is one of the most popular momentum methods in ...
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06/08/2022
Alternating Mirror Descent for Constrained Min-Max Games
In this paper we study two-player bilinear zero-sum games with constrain...
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02/13/2022
Improved analysis for a proximal algorithm for sampling
We study the proximal sampler of Lee, Shen, and Tian (2021) and obtain n...
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01/29/2022
Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions
Distributed machine learning (DML) over time-varying networks can be an ...
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09/24/2021
The Mirror Langevin Algorithm Converges with Vanishing Bias
The technique of modifying the geometry of a problem from Euclidean to H...
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11/19/2019
Fictitious Play: Convergence, Smoothness, and Optimism
We consider the dynamics of two-player zero-sum games, with the goal of ...
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11/04/2019
Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry
We study the Proximal Langevin Algorithm (PLA) for sampling from a proba...
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06/05/2019
Last-iterate convergence rates for min-max optimization
We study the problem of finding min-max solutions for smooth two-input o...
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03/20/2019
Rapid Convergence of the Unadjusted Langevin Algorithm: Log-Sobolev Suffices
We prove a convergence guarantee on the unadjusted Langevin algorithm fo...
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05/03/2018
Convexity of mutual information along the Ornstein-Uhlenbeck flow
We study the convexity of mutual information as a function of time along...
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02/22/2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem
We study sampling as optimization in the space of measures. We focus on ...
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01/22/2018
Convexity of mutual information along the heat flow
We study the convexity of mutual information along the evolution of the ...
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03/14/2016
A Variational Perspective on Accelerated Methods in Optimization
Accelerated gradient methods play a central role in optimization, achiev...
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10/26/2014
Concavity of reweighted Kikuchi approximation
We analyze a reweighted version of the Kikuchi approximation for estimat...
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12/07/2013
Optimal rates for zero-order convex optimization: the power of two function evaluations
We consider derivative-free algorithms for stochastic and non-stochastic...
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07/25/2013