137 citations · 480 across the 19 of their papers we have counts for
19 papers
Understanding the Role of Momentum in Stochastic Gradient Methods
Igor Gitman, Hunter Lang, Pengchuan Zhang +1
The use of momentum in stochastic gradient methods has become a widespread practice in machine learning. Different variants of momentum, including heavy-ball momentum, Nesterov's a…
Using Statistics to Automate Stochastic Optimization
Hunter Lang, Pengchuan Zhang, Lin Xiao
Despite the development of numerous adaptive optimizers, tuning the learning rate of stochastic gradient methods remains a major roadblock to obtaining good practical performance i…
Multi-Level Composite Stochastic Optimization via Nested Variance Reduction
Junyu Zhang, Lin Xiao
We consider multi-level composite optimization problems where each mapping in the composition is the expectation over a family of random smooth mappings or the sum of some finite n…
Hyperbolic Interaction Model For Hierarchical Multi-Label Classification
Boli Chen, Xin Huang, Lin Xiao +2
Different from the traditional classification tasks which assume mutual exclusion of labels, hierarchical multi-label classification (HMLC) aims to assign multiple labels to every…
Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification
Xin Huang, Boli Chen, Lin Xiao +1
Extreme multi-label text classification (XMTC) aims at tagging a document with most relevant labels from an extremely large-scale label set. It is a challenging problem especially…
Secrecy Energy Efficiency Maximization for UAV-Enabled Mobile Relaying
Lin Xiao, Yu Xu, Dingcheng Yang +1
This paper investigates the secrecy energy efficiency (SEE) maximization problem for unmanned aerial vehicle enabled mobile relaying system, where a high-mobility UAV is exploited…