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Improving Local Identifiability in Probabilistic Box Embeddings


Oct 29, 2020
Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Lorraine Li, Andrew McCallum

* Accepted at NeurIPS2020 

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Embedded-State Latent Conditional Random Fields for Sequence Labeling


Sep 28, 2018
Dung Thai, Sree Harsha Ramesh, Shikhar Murty, Luke Vilnis, Andrew McCallum


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Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking


Jul 13, 2018
Shikhar Murty*, Patrick Verga*, Luke Vilnis, Irena Radovanovic, Andrew McCallum

* ACL 2018 

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Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection


May 29, 2018
Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis, Andrew McCallum

* NAACL 2018 

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Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures


May 17, 2018
Luke Vilnis, Xiang Li, Shikhar Murty, Andrew McCallum

* ACL 2018 camera-ready version, 14 pages including appendices 

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Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning


Nov 15, 2017
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum

* ICLR 2018 submission 

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Finer Grained Entity Typing with TypeNet


Nov 15, 2017
Shikhar Murty, Patrick Verga, Luke Vilnis, Andrew McCallum

* Accepted at 6th Workshop on Automated Knowledge Base Construction (AKBC) at NIPS 2017 

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Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling


Aug 02, 2017
Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, Andrew McCallum

* 4 pages, ICML 2017 DeepStruct Workshop 

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Improved Representation Learning for Predicting Commonsense Ontologies


Aug 01, 2017
Xiang Li, Luke Vilnis, Andrew McCallum

* 4 pages, ICML 2017 DeepStruct Workshop 

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Bethe Projections for Non-Local Inference


Nov 28, 2016
Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum

* minor bug fix to appendix. appeared in UAI 2015 

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Generating Sentences from a Continuous Space


May 12, 2016
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, Samy Bengio

* SIGNLL Conference on Computational Natural Language Learning (CONLL), 2016 
* First two authors contributed equally. Work was done when all authors were at Google, Inc 

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Adding Gradient Noise Improves Learning for Very Deep Networks


Nov 21, 2015
Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens


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Learning Dynamic Feature Selection for Fast Sequential Prediction


May 22, 2015
Emma Strubell, Luke Vilnis, Kate Silverstein, Andrew McCallum

* Appears in The 53rd Annual Meeting of the Association for Computational Linguistics, Beijing, China, July 2015 

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Word Representations via Gaussian Embedding


May 01, 2015
Luke Vilnis, Andrew McCallum

* 12 pages, published as conference paper at ICLR 2015 

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Training for Fast Sequential Prediction Using Dynamic Feature Selection


Dec 19, 2014
Emma Strubell, Luke Vilnis, Andrew McCallum

* 5 pages, NIPS Modern ML + NLP Workshop 2014 

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