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04/23/2023
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization
Nowadays, algorithms with fast convergence, small memory footprints, and...
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05/29/2021
A Federated Learning Framework for Nonconvex-PL Minimax Problems
We consider a general class of nonconvex-PL minimax problems in the cros...
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12/02/2020
Partial Gromov-Wasserstein Learning for Partial Graph Matching
Graph matching finds the correspondence of nodes across two graphs and i...
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10/31/2019
A Decentralized Proximal Point-type Method for Saddle Point Problems
In this paper, we focus on solving a class of constrained non-convex non...
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10/21/2019
Efficient Projection-Free Online Methods with Stochastic Recursive Gradient
This paper focuses on projection-free methods for solving smooth Online ...
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10/21/2019
Stochastic Recursive Gradient-Based Methods for Projection-Free Online Learning
This paper focuses on projection-free methods for solving smooth Online ...
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10/21/2019
Aggregated Gradient Langevin Dynamics
In this paper, we explore a general Aggregated Gradient Langevin Dynamic...
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10/10/2019
One Sample Stochastic Frank-Wolfe
One of the beauties of the projected gradient descent method lies in its...
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03/04/2019
A Stochastic Trust Region Method for Non-convex Minimization
We target the problem of finding a local minimum in non-convex finite-su...
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02/19/2019
Stochastic Conditional Gradient++
In this paper, we develop Stochastic Continuous Greedy++ (SCG++), the fi...
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05/25/2018
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
Recently, the decentralized optimization problem is attracting growing a...
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11/13/2016
Accelerated Variance Reduced Block Coordinate Descent
Algorithms with fast convergence, small number of data access, and low p...
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11/12/2016
Riemannian Tensor Completion with Side Information
By restricting the iterate on a nonlinear manifold, the recently propose...
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07/22/2013