Research

November 2, 2022

AMP: Automatically Finding Model ParallelStrategies with Heterogeneity Awareness

NeurIPS 2022

MPCFORMER: FAST, PERFORMANT AND PRIVATE TRANSFORMER INFERENCE WITH MPC

November 2, 2022

AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness

October 13, 2022

A Data-Centric Framework for Composable NLP Workflows

AUTOSYNC: Learning to Synchronize for Data-Parallel Distributed Deep Learning

December 6, 2020

POLLUX: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning

August 27, 2020

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search

October 25, 2019

DRAGONFLY: Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation

Toward Unsupervised Text Content Manipulation

January 28, 2019

Symbolic Graph Reasoning Meets Convolutions

December 3, 2018

Connecting the Dots Between MLE and RL for Sequence Generation

November 24, 2018

Fault Tolerance in Iterative-Convergent Machine Learning

October 18, 2018

Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design.

October 11, 2018

Toward Understanding the Impact of Staleness in Distributed Machine Learning

October 8, 2018

AutoLoss: Learning Discrete Schedules for Alternate Optimization

September 27, 2018

A Statistical Machine Learning Perspective of Deep Learning: Algorithm, Theory, Scalable Computing

Cavs: An Efficient Runtime System for Dynamic Neural Networks