9 citations · 24 across the 13 of their papers we have counts for
13 papers
Proximal bundle methods for hybrid weakly convex composite optimization problems
Jiaming Liang, Renato D. C. Monteiro, Honghao Zhang
This paper establishes the iteration-complexity of proximal bundle methods for solving hybrid (i.e., a blend of smooth and nonsmooth) weakly convex composite optimization (HWC-CO)…
GotFlow3D: Recurrent Graph Optimal Transport for Learning 3D Flow Motion in Particle Tracking
Jiaming Liang, Chao Xu, Shengze Cai
Flow visualization technologies such as particle tracking velocimetry (PTV) are broadly used in understanding the all-pervasiveness three-dimensional (3D) turbulent flow from natur…
Nesterov smoothing for sampling without smoothness
Jiaojiao Fan, Bo Yuan, Jiaming Liang +1
We study the problem of sampling from a target distribution in whose potential is not smooth. Compared with the sampling problem with smooth potentials, this problem…
A single cut proximal bundle method for stochastic convex composite optimization
Jiaming Liang, Vincent Guigues, Renato D. C. Monteiro
This paper considers optimization problems where the objective is the sum of a function given by an expectation and a closed convex composite function, and proposes stochastic comp…
A Proximal Algorithm for Sampling from Non-convex Potentials
Jiaming Liang, Yongxin Chen
We study sampling problems associated with non-convex potentials that meanwhile lack smoothness. In particular, we consider target distributions that satisfy either logarithmic-Sob…
A Proximal Algorithm for Sampling
Jiaming Liang, Yongxin Chen
We study sampling problems associated with potentials that lack smoothness. The potentials can be either convex or non-convex. Departing from the standard smooth setting, the poten…