82 citations · 546 across the 65 of their papers we have counts for
5 papers · 1 filter
Random gradient extrapolation for distributed and stochastic optimization
Guanghui Lan, Yi Zhou
In this paper, we consider a class of finite-sum convex optimization problems defined over a distributed multiagent network with agents connected to a central server. In partic…
Theoretical properties of the global optimizer of two layer neural network
Digvijay Boob, Guanghui Lan
In this paper, we study the problem of optimizing a two-layer artificial neural network that best fits a training dataset. We look at this problem in the setting where the number o…
Dynamic Stochastic Approximation for Multi-stage Stochastic Optimization
Guanghui Lan, Zhiqiang Zhou
In this paper, we consider multi-stage stochastic optimization problems with convex objectives and conic constraints at each stage. We present a new stochastic first-order method,…
Conditional Accelerated Lazy Stochastic Gradient Descent
Guanghui Lan, Sebastian Pokutta, Yi Zhou +1
In this work we introduce a conditional accelerated lazy stochastic gradient descent algorithm with optimal number of calls to a stochastic first-order oracle and convergence rate…
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization
Guanghui Lan, Soomin Lee, Yi Zhou
We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks. Considering that communication is a…