42 citations · 94 across the 15 of their papers we have counts for
5 papers · 1 filter
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…
DTN: A Learning Rate Scheme with Convergence Rate of for SGD
Lam M. Nguyen, Phuong Ha Nguyen, Dzung T. Phan +2
This paper has some inconsistent results, i.e., we made some failed claims because we did some mistakes for using the test criterion for a series. Precisely, our claims on the conv…
A Scale Invariant Flatness Measure for Deep Network Minima
Akshay Rangamani, Nam H. Nguyen, Abhishek Kumar +3
It has been empirically observed that the flatness of minima obtained from training deep networks seems to correlate with better generalization. However, for deep networks with pos…
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…