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06/30/2022
Efficient Entity Candidate Generation for Low-Resource Languages
Candidate generation is a crucial module in entity linking. It also play...
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01/03/2022
Wikipedia Reader Navigation: When Synthetic Data Is Enough
Every day millions of people read Wikipedia. When navigating the vast sp...
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04/18/2021
Low-rank Subspaces for Unsupervised Entity Linking
Entity linking is an important problem with many applications. Most prev...
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04/17/2021
Recursive input and state estimation: A general framework for learning from time series with missing data
Time series with missing data are signals encountered in important setti...
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11/10/2020
Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation
The existing literature on knowledge graph completion mostly focuses on ...
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03/13/2019
MMKG: Multi-Modal Knowledge Graphs
We present MMKG, a collection of three knowledge graphs that contain bot...
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11/12/2018
Learning Representations of Missing Data for Predicting Patient Outcomes
Extracting actionable insight from Electronic Health Records (EHRs) pose...
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10/22/2018
Knowledge Graph Completion to Predict Polypharmacy Side Effects
The polypharmacy side effect prediction problem considers cases in which...
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09/10/2018
Learning Sequence Encoders for Temporal Knowledge Graph Completion
Research on link prediction in knowledge graphs has mainly focused on st...
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06/29/2018
On embeddings as an alternative paradigm for relational learning
Many real-world domains can be expressed as graphs and, more generally, ...
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06/29/2018
On embeddings as alternative paradigm for relational learning
Many real-world domains can be expressed as graphs and, more generally, ...
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05/04/2018
Towards a Spectrum of Graph Convolutional Networks
We present our ongoing work on understanding the limitations of graph co...
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01/30/2018
TransRev: Modeling Reviews as Translations from Users to Items
The text of a review expresses the sentiment a customer has towards a pa...
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09/14/2017
KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features
We present KBLRN, a novel framework for end-to-end learning of knowledge...
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09/07/2017
Representation Learning for Visual-Relational Knowledge Graphs
A visual-relational knowledge graph (KG) is a KG whose entities are asso...
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03/22/2016
Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus
Over the past decade, large-scale supervised learning corpora have enabl...
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06/02/2015