John Chen

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UNIVERSITY OF TORONTO ∙ Rice University

Transformer-Based Models for Question Answering on COVID19

In response to the Kaggle's COVID-19 Open Research Dataset (CORD-19) cha...
01/16/2021 ∙ by Hillary Ngai, et al. ∙ 0 ∙ share

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ImCLR: Implicit Contrastive Learning for Image Classification

Contrastive learning is an effective method for learning visual represen...
11/25/2020 ∙ by John Chen, et al. ∙ 0 ∙ share

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Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP

Clinical machine learning is increasingly multimodal, collected in both ...
11/19/2020 ∙ by John Chen, et al. ∙ 26 ∙ share

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STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge

Empirical risk minimization is perhaps the most influential idea in stat...
06/25/2020 ∙ by Benjamin Coleman, et al. ∙ 6 ∙ share

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Negative sampling in semi-supervised learning

We introduce Negative Sampling in Semi-Supervised Learning (NS3L), a sim...
11/12/2019 ∙ by John Chen, et al. ∙ 0 ∙ share

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Decaying momentum helps neural network training

Momentum is a simple and popular technique in deep learning for gradient...
10/11/2019 ∙ by John Chen, et al. ∙ 0 ∙ share

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Revisiting Consistent Hashing with Bounded Loads

Dynamic load balancing lies at the heart of distributed caching. Here, t...
08/23/2019 ∙ by John Chen, et al. ∙ 0 ∙ share

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Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation

With the resurgence of chat-based dialog systems in consumer and enterpr...
05/11/2018 ∙ by Nicholas Ruiz, et al. ∙ 0 ∙ share

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John Chen

Featured Co-authors

Anshumali Shrivastava

Anastasios Kyrillidis

Frank Rudzicz

Samarth Sinha

Gaurav Gupta

Vatsal Shah

Benjamin Coleman

Safwan Hossain

Xindi Wang

Mahboobeh Parsapoor

Srinivas Bangalore

Transformer-Based Models for Question Answering on COVID19

ImCLR: Implicit Contrastive Learning for Image Classification

Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP

STORM: Foundations of End-to-End Empirical Risk Minimization on the Edge

Negative sampling in semi-supervised learning

Decaying momentum helps neural network training

Revisiting Consistent Hashing with Bounded Loads

Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation