137 citations · 480 across the 19 of their papers we have counts for
8 papers · 1 filter
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…
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…
Learning SMaLL Predictors
Vikas K. Garg, Ofer Dekel, Lin Xiao
We present a new machine learning technique for training small resource-constrained predictors. Our algorithm, the Sparse Multiprototype Linear Learner (SMaLL), is inspired by the…
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
Bo Dai, Albert Shaw, Lihong Li +5
When function approximation is used, solving the Bellman optimality equation with stability guarantees has remained a major open problem in reinforcement learning for decades. The…
Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li +2
Policy evaluation is a crucial step in many reinforcement-learning procedures, which estimates a value function that predicts states' long-term value under a given policy. In this…
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
Jianshu Chen, Ji He, Yelong Shen +5
We develop a fully discriminative learning approach for supervised Latent Dirichlet Allocation (LDA) model using Back Propagation (i.e., BP-sLDA), which maximizes the posterior pro…
Online Classification Using a Voted RDA Method
Tianbing Xu, Jianfeng Gao, Lin Xiao +1
We propose a voted dual averaging method for online classification problems with explicit regularization. This method employs the update rule of the regularized dual averaging (RDA…