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Revisiting BFloat16 Training

Oct 13, 2020
Pedram Zamirai, Jian Zhang, Christopher R. Aberger, Christopher De Sa


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Regulating Accuracy-Efficiency Trade-Offs in Distributed Machine Learning Systems

Jul 13, 2020
A. Feder Cooper, Karen Levy, Christopher De Sa


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Meta-Learning for Variational Inference

Jul 06, 2020
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang


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Asymptotically Optimal Exact Minibatch Metropolis-Hastings

Jun 23, 2020
Ruqi Zhang, A. Feder Cooper, Christopher De Sa


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Neural Manifold Ordinary Differential Equations

Jun 18, 2020
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

* Submitted to NeurIPS 2020 

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Towards Optimal Convergence Rate in Decentralized Stochastic Training

Jun 15, 2020
Yucheng Lu, Zheng Li, Christopher De Sa


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MixML: A Unified Analysis of Weakly Consistent Parallel Learning

Jun 06, 2020
Yucheng Lu, Jack Nash, Christopher De Sa


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Optimizing JPEG Quantization for Classification Networks

Mar 05, 2020
Zhijing Li, Christopher De Sa, Adrian Sampson

* 6 pages, 13 figures, Resource-Constrained Machine Learning (ReCoML) Workshop of MLSys 2020 Conference, Austin, TX, USA, 2020 

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Differentiating through the Fréchet Mean

Mar 05, 2020
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa

* Preprint, 35 pages, 9 figures 

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AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC

Feb 29, 2020
Ruqi Zhang, A. Feder Cooper, Christopher De Sa

* Published at AISTATS 2020 

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Moniqua: Modulo Quantized Communication in Decentralized SGD

Feb 26, 2020
Yucheng Lu, Christopher De Sa


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Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees

Nov 21, 2019
Ruqi Zhang, Christopher De Sa

* Published at NeurIPS 2019 

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Overwrite Quantization: Opportunistic Outlier Handling for Neural Network Accelerators

Oct 13, 2019
Ritchie Zhao, Christopher De Sa, Zhiru Zhang

* Preprint, work in progress. 8 pages 

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PipeMare: Asynchronous Pipeline Parallel DNN Training

Oct 09, 2019
Bowen Yang, Jian Zhang, Jonathan Li, Christopher Ré, Christopher R. Aberger, Christopher De Sa


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QPyTorch: A Low-Precision Arithmetic Simulation Framework

Oct 09, 2019
Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa

* NeurIPS 2019 EMC^2 Workshop on Energy Efficient Machine Learning and Cognitive Computing 

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SWALP : Stochastic Weight Averaging in Low-Precision Training

May 20, 2019
Guandao Yang, Tianyi Zhang, Polina Kirichenko, Junwen Bai, Andrew Gordon Wilson, Christopher De Sa

* Published at ICML 2019 

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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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Distributed Learning with Sublinear Communication

Mar 18, 2019
Jayadev Acharya, Christopher De Sa, Dylan J. Foster, Karthik Sridharan


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Improving Neural Network Quantization without Retraining using Outlier Channel Splitting

Jan 30, 2019
Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang

* 10 pages; fixed incorrect title in metadata 

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Improving Neural Network Quantization using Outlier Channel Splitting

Jan 28, 2019
Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang

* 10 pages 

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Building Efficient Deep Neural Networks with Unitary Group Convolutions

Nov 19, 2018
Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang

* 8 pages, 2 figures 

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The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory

Jun 22, 2018
Dan Alistarh, Christopher De Sa, Nikola Konstantinov

* To be published in PoDC 2018; 18 pages, 1 figure; Changes: added pseudocode for Algorithm 2, some references and corrected typos 

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Minibatch Gibbs Sampling on Large Graphical Models

Jun 15, 2018
Christopher De Sa, Vincent Chen, Wing Wong


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Channel Gating Neural Networks

May 29, 2018
Weizhe Hua, Christopher De Sa, Zhiru Zhang, G. Edward Suh


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Representation Tradeoffs for Hyperbolic Embeddings

Apr 24, 2018
Christopher De Sa, Albert Gu, Christopher Ré, Frederic Sala


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