activity
20172026
most citedConnecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

117 citations · 599 across the 37 of their papers we have counts for

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Showing cs.CLShow all

8 papers · 1 filter

cs.CL2020

RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion

Hao Huang, Guodong Long, Tao Shen +2

Many graph embedding approaches have been proposed for knowledge graph completion via link prediction. Among those, translating embedding approaches enjoy the advantages of light-w…

cs.CL20197 cited

Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction

Yang Li, Guodong Long, Tao Shen +4

Distantly supervised relation extraction intrinsically suffers from noisy labels due to the strong assumption of distant supervision. Most prior works adopt a selective attention m…

cs.CL2019

Temporal Self-Attention Network for Medical Concept Embedding

Xueping Peng, Guodong Long, Tao Shen +3

In longitudinal electronic health records (EHRs), the event records of a patient are distributed over a long period of time and the temporal relations between the events reflect su…

cs.CL2019

Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering

Tao Shen, Xiubo Geng, Tao Qin +3

Many algorithms for Knowledge-Based Question Answering (KBQA) depend on semantic parsing, which translates a question to its logical form. When only weak supervision is provided, i…

cs.CL2018

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,…

cs.CL2018

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…