Research

December 11, 2023

AMP: Automatically Finding Model ParallelStrategies with Heterogeneity Awareness

NeurIPS 2022

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

Cavs: An Efficient Runtime System for Dynamic Neural Networks

On Unifying Deep Generative Models

Litz: An Elastic Framework for High-Performance Distributed Machine Learning

Nonoverlap-Promoting Variable Selection

Deep Generative Models with Learnable Knowledge Constraints

Unsupervised Text Style Transfer using Language Models as Discriminators

Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis

February 16, 2018

Diversity-Promoting Bayesian Learning of Latent Variable Models

November 23, 2017

Structured Generative Adversarial Networks

November 2, 2017

Deep Determinantal Point Process for Large-Scale Multi-Label Classification

October 29, 2017

Near-Orthogonality Regularization in Kernel Methods

August 15, 2017

Uncorrelation and Evenness: A New Diversity-Promoting Regularizer

Learning Latent Space Models with Angular Constraints

Generative Semantic Manipulation with Mask-Contrasting GAN

Poseidon: An Efficient Communication Interface for Distributed Deep Learning on GPU Clusters