375 citations · 2.2k across the 69 of their papers we have counts for
5 papers · 1 filter
Learning Private Neural Language Modeling with Attentive Aggregation
Shaoxiong Ji, Shirui Pan, Guodong Long +3
Mobile keyboard suggestion is typically regarded as a word-level language modeling problem. Centralized machine learning technique requires massive user data collected to train on,…
Tensorized Self-Attention: Efficiently Modeling Pairwise and Global Dependencies Together
Tao Shen, Tianyi Zhou, Guodong Long +2
Neural networks equipped with self-attention have parallelizable computation, light-weight structure, and the ability to capture both long-range and local dependencies. Further, th…
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling
Tao Shen, Tianyi Zhou, Guodong Long +2
Recurrent neural networks (RNN), convolutional neural networks (CNN) and self-attention networks (SAN) are commonly used to produce context-aware representations. RNN can capture l…
Adversarially Regularized Graph Autoencoder for Graph Embedding
Shirui Pan, Ruiqi Hu, Guodong Long +3
Graph embedding is an effective method to represent graph data in a low dimensional space for graph analytics. Most existing embedding algorithms typically focus on preserving the…
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling
Tao Shen, Tianyi Zhou, Guodong Long +3
Many natural language processing tasks solely rely on sparse dependencies between a few tokens in a sentence. Soft attention mechanisms show promising performance in modeling local…