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08/22/2023
EM for Mixture of Linear Regression with Clustered Data
Modern data-driven and distributed learning frameworks deal with diverse...
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06/24/2023
A Unified Approach to Controlling Implicit Regularization via Mirror Descent
Inspired by the remarkable success of deep neural networks, there has be...
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06/22/2023
The Inductive Bias of Flatness Regularization for Deep Matrix Factorization
Recent works on over-parameterized neural networks have shown that the s...
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06/19/2023
Projection-Free Online Convex Optimization via Efficient Newton Iterations
This paper presents new projection-free algorithms for Online Convex Opt...
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04/10/2023
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
We analyze the mixing time of Metropolized Hamiltonian Monte Carlo (HMC)...
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04/08/2023
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry
We study the mixing time of Metropolis-Adjusted Langevin algorithm (MALA...
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03/01/2023
Sampling with Barriers: Faster Mixing via Lewis Weights
We analyze Riemannian Hamiltonian Monte Carlo (RHMC) for sampling a poly...
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12/28/2022
Optimal algorithms for group distributionally robust optimization and beyond
Distributionally robust optimization (DRO) can improve the robustness an...
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11/02/2022
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization
The aim of this paper is to design computationally-efficient and optimal...
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08/16/2022
On the generalization of learning algorithms that do not converge
Generalization analyses of deep learning typically assume that the train...
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04/22/2022
Convergence of the Riemannian Langevin Algorithm
We study the Riemannian Langevin Algorithm for the problem of sampling f...
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08/09/2020
Testing Determinantal Point Processes
Determinantal point processes (DPPs) are popular probabilistic models of...
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11/19/2018
On the Network Visibility Problem
Social media is an attention economy where users are constantly competin...
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11/18/2018
Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification
Identification of latent binary sequences from a pool of noisy observati...
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11/18/2018
