42 citations · 94 across the 7 of their papers we have counts for
5 papers · 1 filter
StepDIRECT -- A Derivative-Free Optimization Method for Stepwise Functions
Dzung T. Phan, Hongsheng Liu, Lam M. Nguyen
In this paper, we propose the StepDIRECT algorithm for derivative-free optimization (DFO), in which the black-box objective function has a stepwise landscape. Our framework is base…
Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization
Quoc Tran-Dinh, Nhan H. Pham, Dzung T. Phan +1
We introduce a hybrid stochastic estimator to design stochastic gradient algorithms for solving stochastic optimization problems. Such a hybrid estimator is a convex combination of…
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization
Nhan H. Pham, Lam M. Nguyen, Dzung T. Phan +1
We propose a new stochastic first-order algorithmic framework to solve stochastic composite nonconvex optimization problems that covers both finite-sum and expectation settings. Ou…
Finite-Sum Smooth Optimization with SARAH
Lam M. Nguyen, Marten van Dijk, Dzung T. Phan +3
The total complexity (measured as the total number of gradient computations) of a stochastic first-order optimization algorithm that finds a first-order stationary point of a finit…
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD
Marten van Dijk, Lam M. Nguyen, Phuong Ha Nguyen +1
We study Stochastic Gradient Descent (SGD) with diminishing step sizes for convex objective functions. We introduce a definitional framework and theory that defines and characteriz…