66 citations · 324 across the 32 of their papers we have counts for
6 papers · 1 filter
A Fast Polynomial-time Primal-Dual Projection Algorithm for Linear Programming
Zhize Li, Wei Zhang, Kees Roos
Traditionally, there are several polynomial algorithms for linear programming including the ellipsoid method, the interior point method and other variants. Recently, Chubanov [Chub…
Learning Two-layer Neural Networks with Symmetric Inputs
Rong Ge, Rohith Kuditipudi, Zhize Li +1
We give a new algorithm for learning a two-layer neural network under a general class of input distributions. Assuming there is a ground-truth two-layer network $$ y = A σ(Wx) + ξ,…
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization
Zhize Li, Jian Li
Anderson acceleration (or Anderson mixing) is an efficient acceleration method for fixed point iterations , e.g., gradient descent can be viewed as iteratively appl…
Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference
Zhize Li, Tianyi Zhang, Shuyu Cheng +2
Gradient-based Monte Carlo sampling algorithms, like Langevin dynamics and Hamiltonian Monte Carlo, are important methods for Bayesian inference. In large-scale settings, full-grad…
Gradient Boosting With Piece-Wise Linear Regression Trees
Yu Shi, Jian Li, Zhize Li
Gradient Boosted Decision Trees (GBDT) is a very successful ensemble learning algorithm widely used across a variety of applications. Recently, several variants of GBDT training al…
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
Zhize Li, Jian Li
We analyze stochastic gradient algorithms for optimizing nonconvex, nonsmooth finite-sum problems. In particular, the objective function is given by the summation of a differentiab…