30 citations · 77 across the 11 of their papers we have counts for
5 papers · 1 filter
Stochastic optimization with decision-dependent distributions
Dmitriy Drusvyatskiy, Lin Xiao
Stochastic optimization problems often involve data distributions that change in reaction to the decision variables. This is the case for example when members of the population res…
Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation
Shoujin Wang, Longbing Cao, Liang Hu +4
A transaction-based recommender system (TBRS) aims to predict the next item by modeling dependencies in transactional data. Generally, two kinds of dependencies considered are intr…
Stochastic Variance-Reduced Prox-Linear Algorithms for Nonconvex Composite Optimization
Junyu Zhang, Lin Xiao
We consider minimization of composite functions of the form , where and are convex functions (which can be nonsmooth) and is a smooth vector mapping. In a…
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck +2
We consider the setting of distributed empirical risk minimization where multiple machines compute the gradients in parallel and a centralized server updates the model parameters.…
Statistical Adaptive Stochastic Gradient Methods
Pengchuan Zhang, Hunter Lang, Qiang Liu +1
We propose a statistical adaptive procedure called SALSA for automatically scheduling the learning rate (step size) in stochastic gradient methods. SALSA first uses a smoothed stoc…