Wei Zhang 
contact information
Research Staff MemberThomas J. Watson Research Center, Yorktown Heights, NY USA +1
9149452747
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2021
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Shyam Ramji, Ulrich Finkler, Susan Malaika, Frederick Reiss
NeurIPS 2021 Datasets and Benchmarks Track
Ruchir Puri, David S. Kung, Geert Janssen, Wei Zhang, Giacomo Domeniconi, Vladimir Zolotov, Julian Dolby, Jie Chen, Mihir Choudhury, Lindsey Decker, Veronika Thost, Luca Buratti, Saurabh Pujar, Shyam Ramji, Ulrich Finkler, Susan Malaika, Frederick Reiss
NeurIPS 2021 Datasets and Benchmarks Track
Asynchronous Decentralized Distributed Training of Acoustic Models
Xiaodong Cui, Wei Zhang, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, David Kung
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021
Xiaodong Cui, Wei Zhang, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, David Kung
IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2021
4-bit Quantization of LSTM-Based Speech Recognition Models
Andrea Fasoli, Chia-Yu Chen, Mauricio Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltan Tuske, Kailash Gopalakrishnan
Interspeech, 2021
Andrea Fasoli, Chia-Yu Chen, Mauricio Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltan Tuske, Kailash Gopalakrishnan
Interspeech, 2021
A(DP)^2SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy
Jie Xu, Wei Zhang, Fei Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-1, Institute of Electrical and Electronics Engineers (IEEE), 2021
Abstract stochastic gradient descent, asynchronous communication, node, differential privacy, deep learning, rate of convergence, distributed computing, inference, computer science, artificial intelligence, process
Jie Xu, Wei Zhang, Fei Wang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-1, Institute of Electrical and Electronics Engineers (IEEE), 2021
Abstract stochastic gradient descent, asynchronous communication, node, differential privacy, deep learning, rate of convergence, distributed computing, inference, computer science, artificial intelligence, process
2020
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Mingrui Liu, Wei Zhang, Youssef Mroueh, Xiaodong Cui, Jarret Ross, Tianbao Yang, Payel Das
Advances in Neural Information Processing Systems (NeurIPS), 2020
Mingrui Liu, Wei Zhang, Youssef Mroueh, Xiaodong Cui, Jarret Ross, Tianbao Yang, Payel Das
Advances in Neural Information Processing Systems (NeurIPS), 2020
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
Advances in Neural Information Processing Systems (NeurIPS), 2020
Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan
Advances in Neural Information Processing Systems (NeurIPS), 2020
Change Detection from Remote Sensing to Guide OpenStreetMap Labeling
Conrad M. Albrecht, Rui Zhang, Xiaodong Cui, Marcus Freitag, Hendrik F. Hamann, Levente J. Klein, Ulrich Finkler, Fernando Marianno, Johannes Schmude, Norman Bobroff, Wei Zhang and Carlo Siebenschuh and Siyuan Lu
International Journal of Geo-Information (IJGI) 9(7), 2020
Conrad M. Albrecht, Rui Zhang, Xiaodong Cui, Marcus Freitag, Hendrik F. Hamann, Levente J. Klein, Ulrich Finkler, Fernando Marianno, Johannes Schmude, Norman Bobroff, Wei Zhang and Carlo Siebenschuh and Siyuan Lu
International Journal of Geo-Information (IJGI) 9(7), 2020
Map Generation from Large Scale Incomplete and Inaccurate Data Labels
Rui Zhang, Conrad Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David Kung, Siyuan Lu
26th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020, (Oral, Applied Data Science Track)
Rui Zhang, Conrad Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David Kung, Siyuan Lu
26th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020, (Oral, Applied Data Science Track)
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies
Xiaodong Cui, Wei Zhang, Ulrich Finkler, George Saon, Michael Picheny, David Kung
IEEE Signal Processing Magazine 37(3), 39-49, 2020
Xiaodong Cui, Wei Zhang, Ulrich Finkler, George Saon, Michael Picheny, David Kung
IEEE Signal Processing Magazine 37(3), 39-49, 2020
Improving Efficiency in Large-Scale Decentralized Distributed Training
Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David Kung, Michael Picheny
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP, Lecture Session)
Wei Zhang, Xiaodong Cui, Abdullah Kayi, Mingrui Liu, Ulrich Finkler, Brian Kingsbury, George Saon, Youssef Mroueh, Alper Buyuktosunoglu, Payel Das, David Kung, Michael Picheny
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP, Lecture Session)
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets
Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang
International Conference on Learning Representations (ICLR), 2020
Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui, Payel Das, Tianbao Yang
International Conference on Learning Representations (ICLR), 2020
2019
Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Mingrui Liu, Youssef Mroueh, Wei Zhang, Xiaodong Cui, Tianbao Yang, Payel Das
Workshop on Smooth Games Optimization and Machine Learning, Advances in Neural Information Processing Systems (NeurIPS) , 2019
Mingrui Liu, Youssef Mroueh, Wei Zhang, Xiaodong Cui, Tianbao Yang, Payel Das
Workshop on Smooth Games Optimization and Machine Learning, Advances in Neural Information Processing Systems (NeurIPS) , 2019
Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition
Khoi-Nguyen C. Mac, Xiaodong Cui, Wei Zhang, Michael Picheny
INTERSPEECH 2019 (oral)
Khoi-Nguyen C. Mac, Xiaodong Cui, Wei Zhang, Michael Picheny
INTERSPEECH 2019 (oral)
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition
Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David Kung, Michael Picheny
INTERSPEECH 2019 (oral)
Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David Kung, Michael Picheny
INTERSPEECH 2019 (oral)
Distributed Deep Learning Strategies For Automatic Speech Regcontion
Wei Zhang, Xiaodong Cui, Ulrich Finkler, Brian Kingsbury, George Saon, David Kung, Michael Picheny
International Conference on Acoustics, Speech, and Signal Processing (ICASSP'2019, Lecture Session)
Wei Zhang, Xiaodong Cui, Ulrich Finkler, Brian Kingsbury, George Saon, David Kung, Michael Picheny
International Conference on Acoustics, Speech, and Signal Processing (ICASSP'2019, Lecture Session)
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks
Xiao Sun, Jungwook Choi, Chia-yu Chen, Naigang Wang, Swagath Venkataramani, Viji Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan
Advances in Neural Information Processing Systems (NeurIPS) , 2019
Xiao Sun, Jungwook Choi, Chia-yu Chen, Naigang Wang, Swagath Venkataramani, Viji Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan
Advances in Neural Information Processing Systems (NeurIPS) , 2019
2018
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
Xiaodong Cui, Wei Zhang, Zoltan Tuske, Michael Picheny
Thirty-second Conference on Neural Information Processing Systems (NIPS'18), 2018
Xiaodong Cui, Wei Zhang, Zoltan Tuske, Michael Picheny
Thirty-second Conference on Neural Information Processing Systems (NIPS'18), 2018
Forecast of Solar Energy Production -- A Deep Learning Approach
Rui Zhang, Minwei Feng, Wei Zhang, Siyuan Lu, Fei Wang
IEEE International Conference on Big Knowledge (ICBK'2018)
Rui Zhang, Minwei Feng, Wei Zhang, Siyuan Lu, Fei Wang
IEEE International Conference on Big Knowledge (ICBK'2018)
Asynchronous Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian*, Wei Zhang*, Ce Zhang, Ji Liu (* Equal Contribution)
International Conference on Machine Learning (ICML'18), Long Oral Paper, 2018
Xiangru Lian*, Wei Zhang*, Ce Zhang, Ji Liu (* Equal Contribution)
International Conference on Machine Learning (ICML'18), Long Oral Paper, 2018
AdaComp: Generalized Residual Gradient Compression for Data-Parallel Distributed Training
Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan
AAAI Conference on Artificial Intelligence (AAAI-18), 2018
Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan
AAAI Conference on Artificial Intelligence (AAAI-18), 2018
2017
Decentralized Distributed Deep Learning
Wei Zhang, Xiangru Lian, Ce Zhang, Ji Liu
Workshop on AI Systems at Symposium on Operating Systems Principles (AISys at SOSP'17), 2017
Wei Zhang, Xiangru Lian, Ce Zhang, Ji Liu
Workshop on AI Systems at Symposium on Operating Systems Principles (AISys at SOSP'17), 2017
Accelerator design for deep learning training
Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopa lakrishnan, Jinwook Oh, Sun il Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang
Design Automation Conference (DAC'17 invited paper), 2017
Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopa lakrishnan, Jinwook Oh, Sun il Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang
Design Automation Conference (DAC'17 invited paper), 2017
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
Neural Information Processing System (NIPS'2017) *Oral Paper (40 out of 3240)*
Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu
Neural Information Processing System (NIPS'2017) *Oral Paper (40 out of 3240)*
Nexus: Bringing Efficient and Scalable Training to Deep Learning Frameworks
Yandog Wang, Li Zhang, Yufei Ren, Wei Zhang
the 25th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2017) *Best Paper Nominee*
Yandog Wang, Li Zhang, Yufei Ren, Wei Zhang
the 25th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2017) *Best Paper Nominee*
GaDei: On Scale-up Training As A Service For Deep Learning
Wei Zhang, Minfei Feng, Yunhui Zheng, Yufei Ren, Yandong Wang, Ji Liu, Peng Liu, Bing Xiang, Li Zhang, Bowen Zhou, Fei Wang
The IEEE International Conference on Data Mining (ICDM'17), 2017
Wei Zhang, Minfei Feng, Yunhui Zheng, Yufei Ren, Yandong Wang, Ji Liu, Peng Liu, Bing Xiang, Li Zhang, Bowen Zhou, Fei Wang
The IEEE International Conference on Data Mining (ICDM'17), 2017
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study
Suyo Gupta*, Wei Zhang*, Fei Wang (*Equal Contribution)
Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) Inivited Paper, 2017
Suyo Gupta*, Wei Zhang*, Fei Wang (*Equal Contribution)
Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) Inivited Paper, 2017
2016
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning:A Systematic Study
Wei Zhang*, Suyog Gupta*, Fei Wang (*Equal contribution)
The IEEE International Conference on Data Mining 2016 (This paper recieves the Best Paper Award Runner-up), IEEE
Wei Zhang*, Suyog Gupta*, Fei Wang (*Equal contribution)
The IEEE International Conference on Data Mining 2016 (This paper recieves the Best Paper Award Runner-up), IEEE
Staleness-Aware Async-SGD for Distributed Deep Learning
Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016, pp. 2350--2356
Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016, pp. 2350--2356
AQuA: Adaptive Quality Analytics
Wei Zhang, Martin Hirzel, David Grove
Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, pp. 169--180, ACM, 2016
Wei Zhang, Martin Hirzel, David Grove
Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, pp. 169--180, ACM, 2016
META: Middleware for Events, Transactions, and Analytics
Matthew Arnold, David Grove, Benjamin Herta, Michael Hind, Martin Hirzel, Arun Iyengar, Louis Mandel, Vijay A. Saraswat, Avraham Shinnar, Jérôme Siméon, Mikio Takeuchi, Olivier Tardieu, Wei Zhang
IBM Journal of Research and Development 60(2-3), 2016
Matthew Arnold, David Grove, Benjamin Herta, Michael Hind, Martin Hirzel, Arun Iyengar, Louis Mandel, Vijay A. Saraswat, Avraham Shinnar, Jérôme Siméon, Mikio Takeuchi, Olivier Tardieu, Wei Zhang
IBM Journal of Research and Development 60(2-3), 2016
X10 and APGAS at Petascale
Olivier Tardieu, Benjamin Herta, David Cunningham, David Grove, Prabhanjan Kambadur, Vijay Saraswat, Avraham Shinnar, Mikio Takeuchi, Mandana Vaziri, Wei Zhang
j-TOPC 2(4), 25:1--25:32, 2016
Abstract
Olivier Tardieu, Benjamin Herta, David Cunningham, David Grove, Prabhanjan Kambadur, Vijay Saraswat, Avraham Shinnar, Mikio Takeuchi, Mandana Vaziri, Wei Zhang
j-TOPC 2(4), 25:1--25:32, 2016
Abstract
2015
Fixing, preventing, and recovering from concurrency bugs
DongDong Deng, GuoLiang Jin, Marc de Kruijf, Ang Li, Ben Liblit, Shan Lu, ShanXiang Qi, JingLei Ren, Karthikeyan Sankaralingam, LinHai Song, YongWei Wu, MingXing Zhang, Wei Zhang, WeiMin Zheng
Science China Information Sciences 58(5), 1--18, 2015
Abstract
DongDong Deng, GuoLiang Jin, Marc de Kruijf, Ang Li, Ben Liblit, Shan Lu, ShanXiang Qi, JingLei Ren, Karthikeyan Sankaralingam, LinHai Song, YongWei Wu, MingXing Zhang, Wei Zhang, WeiMin Zheng
Science China Information Sciences 58(5), 1--18, 2015
Abstract
2014
GLB: Lifeline-based Global Load Balancing Library in X10
Wei Zhang, Olivier Tardieu, David Grove, Benjamin Herta, Tomio Kamada, Vijay Saraswat, Mikio Takeuchi
Proceedings of the First Workshop on Parallel Programming for Analytics Applications, pp. 31--40, ACM, 2014
Abstract
Wei Zhang, Olivier Tardieu, David Grove, Benjamin Herta, Tomio Kamada, Vijay Saraswat, Mikio Takeuchi
Proceedings of the First Workshop on Parallel Programming for Analytics Applications, pp. 31--40, ACM, 2014
Abstract
2013
Efficient Concurrency-bug Detection Across Inputs
Dongdong Deng, Wei Zhang, Shan Lu
Proceedings of the 2013 ACM SIGPLAN International Conference on Object Oriented Programming Systems Languages and Applications, pp. 785--802, ACM
Dongdong Deng, Wei Zhang, Shan Lu
Proceedings of the 2013 ACM SIGPLAN International Conference on Object Oriented Programming Systems Languages and Applications, pp. 785--802, ACM
ConMem: Detecting Crash-Triggering Concurrency Bugs Through an Effect-Oriented Approach
Wei Zhang, Chong Sun, Junghee Lim, Shan Lu, Thomas Reps
ACM Trans. Softw. Eng. Methodol. 22(2), 10:1--10:33, ACM, 2013
Wei Zhang, Chong Sun, Junghee Lim, Shan Lu, Thomas Reps
ACM Trans. Softw. Eng. Methodol. 22(2), 10:1--10:33, ACM, 2013
ConAir: Featherweight Concurrency Bug Recovery via Single-threaded Idempotent Execution
Wei Zhang, Marc de Kruijf, Ang Li, Shan Lu, Karthikeyan Sankaralingam
Proceedings of the Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 113--126, ACM, 2013
Wei Zhang, Marc de Kruijf, Ang Li, Shan Lu, Karthikeyan Sankaralingam
Proceedings of the Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 113--126, ACM, 2013
2012
Understanding the Interleaving-space Overlap Across Inputs and Software Versions
Dongdong Deng, Wei Zhang, Borui Wang, Peisen Zhao, Shan Lu
Proceedings of the 4th USENIX Conference on Hot Topics in Parallelism, pp. 17--17, USENIX Association, 2012
Dongdong Deng, Wei Zhang, Borui Wang, Peisen Zhao, Shan Lu
Proceedings of the 4th USENIX Conference on Hot Topics in Parallelism, pp. 17--17, USENIX Association, 2012
Automated Concurrency-bug Fixing
Guoliang Jin, Wei Zhang, Dongdong Deng, Ben Liblit, Shan Lu
Proceedings of the 10th USENIX Conference on Operating Systems Design and Implementation, pp. 221--236, USENIX Association, 2012
Guoliang Jin, Wei Zhang, Dongdong Deng, Ben Liblit, Shan Lu
Proceedings of the 10th USENIX Conference on Operating Systems Design and Implementation, pp. 221--236, USENIX Association, 2012
2011
ConSeq: Detecting Concurrency Bugs Through Sequential Errors
Wei Zhang, Junghee Lim, Ramya Olichandran, Joel Scherpelz, Guoliang Jin, Shan Lu, Thomas Reps
Proceedings of the Sixteenth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 251--264, ACM, 2011
Wei Zhang, Junghee Lim, Ramya Olichandran, Joel Scherpelz, Guoliang Jin, Shan Lu, Thomas Reps
Proceedings of the Sixteenth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 251--264, ACM, 2011
Automated Atomicity-violation Fixing
Guoliang Jin, Linhai Song, Wei Zhang, Shan Lu, Ben Liblit
Proceedings of the 32Nd ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 389--400, ACM, 2011
Guoliang Jin, Linhai Song, Wei Zhang, Shan Lu, Ben Liblit
Proceedings of the 32Nd ACM SIGPLAN Conference on Programming Language Design and Implementation, pp. 389--400, ACM, 2011
2010
ConMem: Detecting Severe Concurrency Bugs Through an Effect-oriented Approach
Wei Zhang, Chong Sun, Shan Lu
Proceedings of the Fifteenth Edition of ASPLOS on Architectural Support for Programming Languages and Operating Systems, pp. 179--192, ACM, 2010
Wei Zhang, Chong Sun, Shan Lu
Proceedings of the Fifteenth Edition of ASPLOS on Architectural Support for Programming Languages and Operating Systems, pp. 179--192, ACM, 2010