ML Anthology

De Sa, Christopher M

24 publications

NeurIPS 2023 Coneheads: Hierarchy Aware Attention Albert Tseng, Tao Yu, Toni Liu, Christopher M De Sa
NeurIPS 2023 Coordinating Distributed Example Orders for Provably Accelerated Training A. Feder Cooper, Wentao Guo, Duc Khiem Pham, Tiancheng Yuan, Charlie Ruan, Yucheng Lu, Christopher M De Sa
NeurIPS 2023 QuIP: 2-Bit Quantization of Large Language Models with Guarantees Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher M De Sa
NeurIPS 2023 Riemannian Residual Neural Networks Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher M De Sa
NeurIPS 2023 TART: A Plug-and-Play Transformer Module for Task-Agnostic Reasoning Kush Bhatia, Avanika Narayan, Christopher M De Sa, Christopher Ré
NeurIPS 2022 From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Christopher M De Sa, Satyen Kale, Jason Lee, Ayush Sekhari, Karthik Sridharan
NeurIPS 2022 GraB: Finding Provably Better Data Permutations than Random Reshuffling Yucheng Lu, Wentao Guo, Christopher M De Sa
NeurIPS 2022 Model Preserving Compression for Neural Networks Jerry Chee, Megan Flynn (née Renz), Anil Damle, Christopher M De Sa
NeurIPS 2022 Understanding Hyperdimensional Computing for Parallel Single-Pass Learning Tao Yu, Yichi Zhang, Zhiru Zhang, Christopher M De Sa
NeurIPS 2021 Equivariant Manifold Flows Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser Nam Lim, Christopher M De Sa
NeurIPS 2021 Hyperparameter Optimization Is Deceiving Us, and How to Stop It A. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher M De Sa
NeurIPS 2021 Representing Hyperbolic Space Accurately Using Multi-Component Floats Tao Yu, Christopher M De Sa
NeurIPS 2020 Asymptotically Optimal Exact Minibatch Metropolis-Hastings Ruqi Zhang, A. Feder Cooper, Christopher M De Sa
NeurIPS 2020 Neural Manifold Ordinary Differential Equations Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser Nam Lim, Christopher M De Sa
NeurIPS 2020 Random Reshuffling Is Not Always Better Christopher M De Sa
NeurIPS 2019 Channel Gating Neural Networks Weizhe Hua, Yuan Zhou, Christopher M De Sa, Zhiru Zhang, G. Edward Suh
NeurIPS 2019 Dimension-Free Bounds for Low-Precision Training Zheng Li, Christopher M De Sa
NeurIPS 2019 Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models Tao Yu, Christopher M De Sa
NeurIPS 2019 Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees Ruqi Zhang, Christopher M De Sa
NeurIPS 2017 Gaussian Quadrature for Kernel Features Tri Dao, Christopher M De Sa, Christopher Ré
NeurIPS 2016 Data Programming: Creating Large Training Sets, Quickly Alexander J Ratner, Christopher M De Sa, Sen Wu, Daniel Selsam, Christopher Ré
NeurIPS 2016 Scan Order in Gibbs Sampling: Models in Which It Matters and Bounds on How Much Bryan D He, Christopher M De Sa, Ioannis Mitliagkas, Christopher Ré
NeurIPS 2015 Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width Christopher M De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré
NeurIPS 2015 Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms Christopher M De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré, Christopher Ré