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Transformer-Based Models for Question Answering on COVID19
In response to the Kaggle's COVID-19 Open Research Dataset (CORD-19) cha...
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ImCLR: Implicit Contrastive Learning for Image Classification
Contrastive learning is an effective method for learning visual represen...
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Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
Clinical machine learning is increasingly multimodal, collected in both ...
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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...
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Negative sampling in semi-supervised learning
We introduce Negative Sampling in Semi-Supervised Learning (NS3L), a sim...
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Decaying momentum helps neural network training
Momentum is a simple and popular technique in deep learning for gradient...
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Revisiting Consistent Hashing with Bounded Loads
Dynamic load balancing lies at the heart of distributed caching. Here, t...
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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...
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