3 papers
math.OC2020
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization
Digvijay Boob, Qi Deng, Guanghui Lan +1
Nonconvex sparse models have received significant attention in high-dimensional machine learning. In this paper, we study a new model consisting of a general convex or nonconvex ob…
math.OC2019
Efficiency of Coordinate Descent Methods For Structured Nonconvex Optimization
Qi Deng, Chenghao Lan
Novel coordinate descent (CD) methods are proposed for minimizing nonconvex functions consisting of three terms: (i) a continuously differentiable term, (ii) a simple convex term,…
stat.ML2018
Optimal Adaptive and Accelerated Stochastic Gradient Descent
Qi Deng, Yi Cheng, Guanghui Lan
Stochastic gradient descent (\textsc{Sgd}) methods are the most powerful optimization tools in training machine learning and deep learning models. Moreover, acceleration (a.k.a. mo…