11 citations · 19 across the 2 of their papers we have counts for
8 papers
A Variational Inequality Approach to Bayesian Regression Games
Wenshuo Guo, Michael I. Jordan, Tianyi Lin
Bayesian regression games are a special class of two-player general-sum Bayesian games in which the learner is partially informed about the adversary's objective through a Bayesian…
Sparsemax and Relaxed Wasserstein for Topic Sparsity
Tianyi Lin, Zhiyue Hu, Xin Guo
Topic sparsity refers to the observation that individual documents usually focus on several salient topics instead of covering a wide variety of topics, and a real topic adopts a n…
A Unified Adaptive Tensor Approximation Scheme to Accelerate Composite Convex Optimization
Bo Jiang, Tianyi Lin, Shuzhong Zhang
In this paper, we propose a unified two-phase scheme to accelerate any high-order regularized tensor approximation approach on the smooth part of a composite convex optimization mo…
Improved Sample Complexity for Stochastic Compositional Variance Reduced Gradient
Tianyi Lin, Chenyou Fan, Mengdi Wang +1
Convex composition optimization is an emerging topic that covers a wide range of applications arising from stochastic optimal control, reinforcement learning and multi-stage stocha…
An ADMM-Based Interior-Point Method for Large-Scale Linear Programming
Tianyi Lin, Shiqian Ma, Yinyu Ye +1
We propose a new framework to implement interior point method (IPM) to solve very large linear programs (LP). Traditional IPMs typically use Newton's method to approximately solve…
Improved Oracle Complexity of Variance Reduced Methods for Nonsmooth Convex Stochastic Composition Optimization
Tianyi Lin, Chenyou Fan, Mengdi Wang
We consider the nonsmooth convex composition optimization problem where the objective is a composition of two finite-sum functions and analyze stochastic compositional variance red…