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Christopher De Sa

Showing results (1-10 of 16) with videos related to

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JMLR Workshop and Conference Proceedings|March 28, 2017
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs SamplingChristopher De Sa, Kunle Olukotun, Christopher Ré
Advances in Neural Information Processing Systems|February 6, 2018
Gaussian Quadrature for Kernel FeaturesTri Dao, Christopher De Sa, Christopher Ré
Proceedings of Machine Learning Research|May 28, 2019
Representation Tradeoffs for Hyperbolic EmbeddingsChristopher De Sa, Albert Gu, Christopher Ré, et al.
Advances in Neural Information Processing Systems|June 10, 2016
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy WidthChristopher De Sa, Ce Zhang, Kunle Olukotun, et al.
Advances in Neural Information Processing Systems|March 28, 2017
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How MuchBryan He, Christopher De Sa, Ioannis Mitliagkas, et al.
Proceedings. International Symposium on Computer Architecture|February 3, 2018
Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient DescentChristopher De Sa, Matthew Feldman, Christopher Ré, et al.
Advances in Neural Information Processing Systems|October 17, 2024
QuIP: 2-Bit Quantization of Large Language Models With GuaranteesJerry Chee, Yaohui Cai, Volodymyr Kuleshov, et al.
Advances in Neural Information Processing Systems|June 23, 2016
Taming the Wild: A Unified Analysis of Hogwild!-Style AlgorithmsChristopher De Sa, Ce Zhang, Kunle Olukotun, et al.
Proceedings of Machine Learning Research|June 13, 2019
Accelerated Stochastic Power IterationChristopher De Sa, Bryan He, Ioannis Mitliagkas, et al.
Proceedings of Machine Learning Research|September 2, 2025
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice CodebooksAlbert Tseng, Jerry Chee, Qingyao Sun, et al.
Pageof 2

Showing results (1-10 of 16) with videos related to

Sort By:
Pageof 2
JMLR Workshop and Conference Proceedings|March 28, 2017
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs SamplingChristopher De Sa, Kunle Olukotun, Christopher Ré
Advances in Neural Information Processing Systems|February 6, 2018
Gaussian Quadrature for Kernel FeaturesTri Dao, Christopher De Sa, Christopher Ré
Proceedings of Machine Learning Research|May 28, 2019
Representation Tradeoffs for Hyperbolic EmbeddingsChristopher De Sa, Albert Gu, Christopher Ré, et al.
Advances in Neural Information Processing Systems|June 10, 2016
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy WidthChristopher De Sa, Ce Zhang, Kunle Olukotun, et al.
Advances in Neural Information Processing Systems|March 28, 2017
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How MuchBryan He, Christopher De Sa, Ioannis Mitliagkas, et al.
Proceedings. International Symposium on Computer Architecture|February 3, 2018
Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient DescentChristopher De Sa, Matthew Feldman, Christopher Ré, et al.
Advances in Neural Information Processing Systems|October 17, 2024
QuIP: 2-Bit Quantization of Large Language Models With GuaranteesJerry Chee, Yaohui Cai, Volodymyr Kuleshov, et al.
Advances in Neural Information Processing Systems|June 23, 2016
Taming the Wild: A Unified Analysis of Hogwild!-Style AlgorithmsChristopher De Sa, Ce Zhang, Kunle Olukotun, et al.
Proceedings of Machine Learning Research|June 13, 2019
Accelerated Stochastic Power IterationChristopher De Sa, Bryan He, Ioannis Mitliagkas, et al.
Proceedings of Machine Learning Research|September 2, 2025
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice CodebooksAlbert Tseng, Jerry Chee, Qingyao Sun, et al.
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