De Sa, Chris

7 publications

NeurIPS 2024 Diffusion Models with Learned Adaptive Noise Subham Sekhar Sahoo, Aaron Gokaslan, Chris De Sa, Volodymyr Kuleshov

ICML 2019 A Kernel Theory of Modern Data Augmentation Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher Re

ICML 2019 Distributed Learning with Sublinear Communication Jayadev Acharya, Chris De Sa, Dylan Foster, Karthik Sridharan

ICML 2019 Improving Neural Network Quantization Without Retraining Using Outlier Channel Splitting Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Chris De Sa, Zhiru Zhang

ICML 2019 SWALP : Stochastic Weight Averaging in Low Precision Training Guandao Yang, Tianyi Zhang, Polina Kirichenko, Junwen Bai, Andrew Gordon Wilson, Chris De Sa

ICML 2018 Minibatch Gibbs Sampling on Large Graphical Models Chris De Sa, Vincent Chen, Wing Wong

ICML 2018 Representation Tradeoffs for Hyperbolic Embeddings Frederic Sala, Chris De Sa, Albert Gu, Christopher Re