De Sa, Christopher

36 publications

ICLR 2025 Compute-Optimal LLMs Provably Generalize Better with Scale Marc Anton Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J Zico Kolter, Andrew Gordon Wilson

NeurIPS 2025 Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Eleni Triantafillou, Peter Kairouz, Nicole Elyse Mitchell, Niloofar Mireshghallah, Abigail Z. Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, Danah Boyd, Yejin Choi, Sanmi Koyejo, Fernando Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Miles Brundage, David Bau, Seth Neel, Hanna Wallach, Amy B. Cyphert, Mark Lemley, Nicolas Papernot, Katherine Lee

ICLR 2025 Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity Wentao Guo, Jikai Long, Yimeng Zeng, Zirui Liu, Xinyu Yang, Yide Ran, Jacob R. Gardner, Osbert Bastani, Christopher De Sa, Xiaodong Yu, Beidi Chen, Zhaozhuo Xu

AAAI 2024 Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification A. Feder Cooper, Katherine Lee, Madiha Zahrah Choksi, Solon Barocas, Christopher De Sa, James Grimmelmann, Jon M. Kleinberg, Siddhartha Sen, Baobao Zhang

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

NeurIPSW 2024 Diffusion Models with Learned Adaptive Noise Processes Subham Sekhar Sahoo, Aaron Gokaslan, Christopher De Sa, Volodymyr Kuleshov

TMLR 2024 ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers Junjie Yin, Jiahao Dong, Yingheng Wang, Christopher De Sa, Volodymyr Kuleshov

NeurIPS 2024 QTIP: Quantization with Trellises and Incoherence Processing Albert Tseng, Qingyao Sun, David Hou, Christopher De Sa

ICML 2024 QuIP$#$: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa

NeurIPS 2024 Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices Andres Potapczynski, Shikai Qiu, Marc Finzi, Christopher Ferri, Zixi Chen, Micah Goldblum, C. Bayan Bruss, Christopher De Sa, Andrew Gordon Wilson

ICLR 2024 Shadow Cones: A Generalized Framework for Partial Order Embeddings Tao Yu, Toni J.B. Liu, Albert Tseng, Christopher De Sa

ICMLW 2024 Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity Wentao Guo, Jikai Long, Yimeng Zeng, Zirui Liu, Xinyu Yang, Yide Ran, Jacob R. Gardner, Osbert Bastani, Christopher De Sa, Xiaodong Yu, Beidi Chen, Zhaozhuo Xu

ICMLW 2024 Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity Wentao Guo, Jikai Long, Yimeng Zeng, Zirui Liu, Xinyu Yang, Yide Ran, Jacob R. Gardner, Osbert Bastani, Christopher De Sa, Xiaodong Yu, Beidi Chen, Zhaozhuo Xu

ICML 2023 CocktailSGD: Fine-Tuning Foundation Models over 500Mbps Networks Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Re, Ce Zhang

JMLR 2023 Decentralized Learning: Theoretical Optimality and Practical Improvements Yucheng Lu, Christopher De Sa

UAI 2023 Inference for Probabilistic Dependency Graphs Oliver E. Richardson, Joseph Y. Halpern, Christopher De Sa

ICML 2023 InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, Volodymyr Kuleshov

ICLR 2023 Maximizing Communication Efficiency for Large-Scale Training via 0/1 Adam Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He

ICLR 2023 Random Laplacian Features for Learning with Hyperbolic Space Tao Yu, Christopher De Sa

ICML 2023 STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh

NeurIPSW 2023 TART: A Plug-and-Play Transformer Module for Task-Agnostic Reasoning Kush Bhatia, Avanika Narayan, Christopher De Sa, Christopher Re

ICLR 2022 A General Analysis of Example-Selection for Stochastic Gradient Descent Yucheng Lu, Si Yi Meng, Christopher De Sa

ICLR 2022 How Low Can We Go: Trading Memory for Error in Low-Precision Training Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell

ICML 2022 Low-Precision Stochastic Gradient Langevin Dynamics Ruqi Zhang, Andrew Gordon Wilson, Christopher De Sa

AISTATS 2021 Meta-Learning Divergences for Variational Inference Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang

ICMLW 2021 Equivariant Manifold Flows Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

ICML 2021 Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision Johan Björck, Xiangyu Chen, Christopher De Sa, Carla P Gomes, Kilian Weinberger

ICML 2021 Optimal Complexity in Decentralized Training Yucheng Lu, Christopher De Sa

ICML 2021 Variance Reduced Training with Stratified Sampling for Forecasting Models Yucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster

AISTATS 2020 AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC Ruqi Zhang, A. Feder Cooper, Christopher De Sa

ICML 2020 Differentiating Through the Fréchet Mean Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa

ICML 2020 Moniqua: Modulo Quantized Communication in Decentralized SGD Yucheng Lu, Christopher De Sa

AISTATS 2018 Accelerated Stochastic Power Iteration Peng Xu, Bryan D. He, Christopher De Sa, Ioannis Mitliagkas, Christopher Ré

IJCAI 2017 Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling Christopher De Sa, Kunle Olukotun, Christopher Ré

ICML 2016 Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling Christopher De Sa, Chris Re, Kunle Olukotun

ICML 2015 Global Convergence of Stochastic Gradient Descent for Some Non-Convex Matrix Problems Christopher De Sa, Christopher Re, Kunle Olukotun