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On the Iteration Complexity of Smoothed Proximal ALM for Nonconvex Optimization Problem with Convex Constraints
It is well-known that the lower bound of iteration complexity for solving nonconvex unconstrained optimization problems is …
Jiawei Zhang, Wenqiang Pu, Zhi-Quan Luo
Last updated on Oct, 2024
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A Global Dual Error Bound and Its Application to the Analysis of Linearly Constrained Nonconvex Optimization
Error bound analysis, which estimates the distance of a point to the solution set of an optimization problem4 using the optimality …
Jiawei Zhang, Zhi-Quan Luo
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Decentralized Non-Convex Learning With Linearly Coupled Constraints: Algorithm Designs and Application to Vertical Learning Problem
Motivated by the need for decentralized learning, this paper aims at designing a distributed algorithm for solving nonconvex problems …
Jiawei Zhang, Songyang Ge, Tsung-Hui Chang, Zhi-Quan Luo
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Distributed Stochastic Consensus Optimization With Momentum for Nonconvex Nonsmooth Problems
While many distributed optimization algorithms have been proposed for solving smooth or convex problems over the networks, few of them …
Zhiguo Wang, Jiawei Zhang, Tsung-Hui Chang, Jian Li, Zhi-Quan Luo
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A Proximal Alternating Direction Method of Multiplier for Linearly Constrained Nonconvex Minimization
Consider the minimization of a nonconvex differentiable function over a bounded polyhedron. A popular primal-dual first-order method …
Jiawei Zhang, Zhi-Quan Luo
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