Wei Dai

According to our database1, Wei Dai authored at least 27 papers between 2013 and 2019.

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Bibliography

2019
Neural Architecture Search for Adversarial Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Toward Understanding the Impact of Staleness in Distributed Machine Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters.
J. Mach. Learn. Res., 2018

Cavs: An Efficient Runtime System for Dynamic Neural Networks.
Proceedings of the 2018 USENIX Annual Technical Conference, 2018

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018

Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018

Classification of Breast Cancer Histopathological Images using Convolutional Neural Networks with Hierarchical Loss and Global Pooling.
Proceedings of the Image Analysis and Recognition - 15th International Conference, 2018

2017
Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks.
CoRR, 2017

SCAN: Structure Correcting Adversarial Network for Chest X-rays Organ Segmentation.
CoRR, 2017

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters.
Proceedings of the 2017 USENIX Annual Technical Conference, 2017

PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Dual Motion GAN for Future-Flow Embedded Video Prediction.
Proceedings of the IEEE International Conference on Computer Vision, 2017

2016
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms.
Proceedings of the 33nd International Conference on Machine Learning, 2016

STRADS: a distributed framework for scheduled model parallel machine learning.
Proceedings of the Eleventh European Conference on Computer Systems, 2016

Addressing the straggler problem for iterative convergent parallel ML.
Proceedings of the Seventh ACM Symposium on Cloud Computing, 2016

On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Petuum: A New Platform for Distributed Machine Learning on Big Data.
IEEE Trans. Big Data, 2015

Strategies and Principles of Distributed Machine Learning on Big Data.
CoRR, 2015

LightLDA: Big Topic Models on Modest Computer Clusters.
Proceedings of the 24th International Conference on World Wide Web, 2015

Managed communication and consistency for fast data-parallel iterative analytics.
Proceedings of the Sixth ACM Symposium on Cloud Computing, 2015

High-Performance Distributed ML at Scale through Parameter Server Consistency Models.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
LightLDA: Big Topic Models on Modest Compute Clusters.
CoRR, 2014

Exploiting Bounded Staleness to Speed Up Big Data Analytics.
Proceedings of the 2014 USENIX Annual Technical Conference, 2014

Exploiting iterative-ness for parallel ML computations.
Proceedings of the ACM Symposium on Cloud Computing, 2014

2013
Consistent Bounded-Asynchronous Parameter Servers for Distributed ML.
CoRR, 2013

Petuum: A Framework for Iterative-Convergent Distributed ML.
CoRR, 2013


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