171 citations · 280 across the 12 of their papers we have counts for
3 papers · 1 filter
Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics
Daniel Kang, Ankit Mathur, Teja Veeramacheneni +2
While deep neural networks (DNNs) are an increasingly popular way to query large corpora of data, their significant runtime remains an active area of research. As a result, researc…
Improved Natural Language Generation via Loss Truncation
Daniel Kang, Tatsunori Hashimoto
Neural language models are usually trained to match the distributional properties of a large-scale corpus by minimizing the log loss. While straightforward to optimize, this approa…
Model Assertions for Monitoring and Improving ML Models
Daniel Kang, Deepti Raghavan, Peter Bailis +1
ML models are increasingly deployed in settings with real world interactions such as vehicles, but unfortunately, these models can fail in systematic ways. To prevent errors, ML en…