Showing 1–20 of 82 results
/ Date/ Name
Oct 9, 2019PipeMare: Asynchronous Pipeline Parallel DNN TrainingJun 22, 2015Taming the Wild: A Unified Analysis of Hogwild!-Style AlgorithmsMar 9, 2018High-Accuracy Low-Precision TrainingJun 15, 2018Minibatch Gibbs Sampling on Large Graphical ModelsNov 5, 2014Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix ProblemsOct 2, 2015Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy WidthMar 16, 2018A Kernel Theory of Modern Data AugmentationFeb 24, 2016Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs SamplingJan 27, 2023Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair ClassificationJul 4, 2020Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML SystemsJul 25, 2023QuIP: 2-Bit Quantization of Large Language Models With GuaranteesJul 18, 2022MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-PointFeb 14, 2022Random Laplacian Features for Learning with Hyperbolic SpaceFeb 26, 2020Moniqua: Modulo Quantized Communication in Decentralized SGDJun 18, 2020Neural Manifold Ordinary Differential EquationsOct 13, 2020Revisiting BFloat16 TrainingFeb 5, 2021Hyperparameter Optimization Is Deceiving Us, and How to Stop ItJul 10, 2017Accelerated Stochastic Power IterationApr 10, 2018Representation Tradeoffs for Hyperbolic EmbeddingsJun 10, 2016Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much