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2020 – today
- 2024
[c37]Khe Chai Sim, Zhouyuan Huo, Tsendsuren Munkhdalai, Nikhil Siddhartha, Adam Stooke, Zhong Meng, Bo Li, Tara N. Sainath:
A Comparison of Parameter-Efficient ASR Domain Adaptation Methods for Universal Speech and Language Models. ICASSP 2024: 6900-6904- [c36]Shefali Garg, Zhouyuan Huo, Khe Chai Sim, Suzan Schwartz, Mason Chua, Alëna Aksënova, Tsendsuren Munkhdalai, Levi King, Darryl Wright, Zion Mengesha, Dongseong Hwang, Tara N. Sainath, Françoise Beaufays, Pedro Moreno Mengibar:
Improving Speech Recognition for African American English with Audio Classification. ICASSP 2024: 12356-12360 - 2023
- [j5]Bin Gu
, Chenkang Zhang, Zhouyuan Huo, Heng Huang:
A new large-scale learning algorithm for generalized additive models. Mach. Learn. 112(9): 3077-3104 (2023) - [c35]Zhouyuan Huo, Khe Chai Sim, Bo Li, Dongseong Hwang, Tara N. Sainath, Trevor Strohman:
Resource-Efficient Transfer Learning from Speech Foundation Model Using Hierarchical Feature Fusion. ICASSP 2023: 1-5 - [c34]Bo Li, Dongseong Hwang, Zhouyuan Huo, Junwen Bai, Guru Prakash, Tara N. Sainath, Khe Chai Sim, Yu Zhang, Wei Han, Trevor Strohman, Françoise Beaufays:
Efficient Domain Adaptation for Speech Foundation Models. ICASSP 2023: 1-5 - [c33]Zhouyuan Huo, Khe Chai Sim, Dongseong Hwang, Tsendsuren Munkhdalai, Tara N. Sainath, Pedro Moreno Mengibar:
Re-investigating the Efficient Transfer Learning of Speech Foundation Model using Feature Fusion Methods. INTERSPEECH 2023: 556-560 - [c32]Xiaohan Zhao, Hualin Zhang, Zhouyuan Huo, Bin Gu:
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism. NeurIPS 2023 - [i30]Bo Li, Dongseong Hwang, Zhouyuan Huo, Junwen Bai, Guru Prakash, Tara N. Sainath, Khe Chai Sim, Yu Zhang, Wei Han, Trevor Strohman, Françoise Beaufays:
Efficient Domain Adaptation for Speech Foundation Models. CoRR abs/2302.01496 (2023) - [i29]Shefali Garg, Zhouyuan Huo, Khe Chai Sim, Suzan Schwartz, Mason Chua, Alëna Aksënova, Tsendsuren Munkhdalai, Levi King, Darryl Wright, Zion Mengesha, Dongseong Hwang, Tara N. Sainath, Françoise Beaufays, Pedro Moreno Mengibar:
Improving Speech Recognition for African American English With Audio Classification. CoRR abs/2309.09996 (2023) - 2022
- [j4]Bin Gu, Zhiyuan Dang, Zhouyuan Huo, Cheng Deng, Heng Huang:
Scaling Up Generalized Kernel Methods. IEEE Trans. Pattern Anal. Mach. Intell. 44(7): 3767-3778 (2022) - [j3]Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang:
Privacy-Preserving Asynchronous Vertical Federated Learning Algorithms for Multiparty Collaborative Learning. IEEE Trans. Neural Networks Learn. Syst. 33(11): 6103-6115 (2022) - [c31]Dongseong Hwang, Ananya Misra, Zhouyuan Huo, Nikhil Siddhartha, Shefali Garg, David Qiu, Khe Chai Sim, Trevor Strohman, Françoise Beaufays, Yanzhang He:
Large-Scale ASR Domain Adaptation Using Self- and Semi-Supervised Learning. ICASSP 2022: 6627-6631 - [c30]Dongseong Hwang, Khe Chai Sim, Zhouyuan Huo, Trevor Strohman:
Pseudo Label Is Better Than Human Label. INTERSPEECH 2022: 1421-1425 - [c29]Zhouyuan Huo, Dongseong Hwang, Khe Chai Sim, Shefali Garg, Ananya Misra, Nikhil Siddhartha, Trevor Strohman, Françoise Beaufays:
Incremental Layer-Wise Self-Supervised Learning for Efficient Unsupervised Speech Domain Adaptation On Device. INTERSPEECH 2022: 4845-4849 - [c28]Tara N. Sainath, Rohit Prabhavalkar, Ankur Bapna, Yu Zhang, Zhouyuan Huo, Zhehuai Chen, Bo Li, Weiran Wang, Trevor Strohman:
JOIST: A Joint Speech and Text Streaming Model for ASR. SLT 2022: 52-59 - [i28]Dongseong Hwang, Khe Chai Sim, Zhouyuan Huo, Trevor Strohman:
Pseudo Label Is Better Than Human Label. CoRR abs/2203.12668 (2022) - [i27]Tara N. Sainath, Rohit Prabhavalkar, Ankur Bapna, Yu Zhang, Zhouyuan Huo, Zhehuai Chen, Bo Li, Weiran Wang, Trevor Strohman:
JOIST: A Joint Speech and Text Streaming Model For ASR. CoRR abs/2210.07353 (2022) - [i26]Zhouyuan Huo, Khe Chai Sim, Bo Li, Dongseong Hwang, Tara N. Sainath, Trevor Strohman:
Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion. CoRR abs/2211.02712 (2022) - 2021
- [j2]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [c27]Zhouyuan Huo, Bin Gu, Heng Huang:
Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling. AAAI 2021: 7883-7890 - [c26]An Xu, Zhouyuan Huo, Heng Huang:
Step-Ahead Error Feedback for Distributed Training with Compressed Gradient. AAAI 2021: 10478-10486 - [c25]Ananya Misra, Dongseong Hwang, Zhouyuan Huo, Shefali Garg, Nikhil Siddhartha, Arun Narayanan, Khe Chai Sim:
A Comparison of Supervised and Unsupervised Pre-Training of End-to-End Models. Interspeech 2021: 731-735 - [c24]Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith:
On Large-Cohort Training for Federated Learning. NeurIPS 2021: 20461-20475 - [i25]Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith:
On Large-Cohort Training for Federated Learning. CoRR abs/2106.07820 (2021) - [i24]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i23]Zhouyuan Huo, Dongseong Hwang, Khe Chai Sim, Shefali Garg, Ananya Misra, Nikhil Siddhartha, Trevor Strohman, Françoise Beaufays:
Incremental Layer-wise Self-Supervised Learning for Efficient Speech Domain Adaptation On Device. CoRR abs/2110.00155 (2021) - [i22]Dongseong Hwang, Ananya Misra, Zhouyuan Huo, Nikhil Siddhartha, Shefali Garg, David Qiu, Khe Chai Sim, Trevor Strohman, Françoise Beaufays, Yanzhang He:
Large-scale ASR Domain Adaptation using Self- and Semi-supervised Learning. CoRR abs/2110.00165 (2021) - 2020
- [j1]Bin Gu, Wenhan Xian, Zhouyuan Huo, Cheng Deng, Heng Huang:
A Unified q-Memorization Framework for Asynchronous Stochastic Optimization. J. Mach. Learn. Res. 21: 190:1-190:53 (2020) - [c23]An Xu, Zhouyuan Huo, Heng Huang:
On the Acceleration of Deep Learning Model Parallelism With Staleness. CVPR 2020: 2085-2094 - [i21]Zhouyuan Huo, Bin Gu, Heng Huang:
Large Batch Training Does Not Need Warmup. CoRR abs/2002.01576 (2020) - [i20]Zhouyuan Huo, Qian Yang, Bin Gu, Lawrence Carin, Heng Huang:
Faster On-Device Training Using New Federated Momentum Algorithm. CoRR abs/2002.02090 (2020) - [i19]An Xu, Zhouyuan Huo, Heng Huang:
Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training. CoRR abs/2002.11082 (2020) - [i18]An Xu, Zhouyuan Huo, Heng Huang:
Exploit Where Optimizer Explores via Residuals. CoRR abs/2004.05298 (2020) - [i17]An Xu, Zhouyuan Huo, Heng Huang:
Training Faster with Compressed Gradient. CoRR abs/2008.05823 (2020) - [i16]Bin Gu, An Xu, Zhouyuan Huo, Cheng Deng, Heng Huang:
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning. CoRR abs/2008.06233 (2020)
2010 – 2019
- 2019
- [c22]Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang:
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. AAAI 2019: 1503-1510 - [c21]Bin Gu, Zhouyuan Huo, Heng Huang:
Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy. AAAI 2019: 3697-3704 - [c20]Liang Yang, Hao Jiang, Zhouyuan Huo, Jizhong Xiao:
Visual-GPS: Ego-Downward and Ambient Video Based Person Location Association. CVPR Workshops 2019: 371-380 - [c19]Qian Yang, Zhouyuan Huo, Dinghan Shen, Yong Cheng, Wenlin Wang, Guoyin Wang, Lawrence Carin:
An End-to-End Generative Architecture for Paraphrase Generation. EMNLP/IJCNLP (1) 2019: 3130-3140 - [c18]Qian Yang, Zhouyuan Huo, Wenlin Wang, Heng Huang, Lawrence Carin:
Ouroboros: On Accelerating Training of Transformer-Based Language Models. NeurIPS 2019: 5520-5530 - [i15]Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang:
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. CoRR abs/1902.06158 (2019) - [i14]An Xu, Zhouyuan Huo, Heng Huang:
Diversely Stale Parameters for Efficient Training of CNNs. CoRR abs/1909.02625 (2019) - [i13]Qian Yang, Zhouyuan Huo, Wenlin Wang, Heng Huang, Lawrence Carin:
Ouroboros: On Accelerating Training of Transformer-Based Language Models. CoRR abs/1909.06695 (2019) - [i12]Zhouyuan Huo, Heng Huang:
Straggler-Agnostic and Communication-Efficient Distributed Primal-Dual Algorithm for High-Dimensional Data Mining. CoRR abs/1910.04235 (2019) - [i11]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019) - 2018
- [c17]Bin Gu, Miao Xin, Zhouyuan Huo, Heng Huang:
Asynchronous Doubly Stochastic Sparse Kernel Learning. AAAI 2018: 3085-3092 - [c16]Bin Gu, De Wang, Zhouyuan Huo, Heng Huang:
Inexact Proximal Gradient Methods for Non-Convex and Non-Smooth Optimization. AAAI 2018: 3093-3100 - [c15]Zhouyuan Huo, Bin Gu, Ji Liu, Heng Huang:
Accelerated Method for Stochastic Composition Optimization With Nonsmooth Regularization. AAAI 2018: 3287-3294 - [c14]Bin Gu, Zhouyuan Huo, Heng Huang:
Asynchronous Doubly Stochastic Group Regularized Learning. AISTATS 2018: 1791-1800 - [c13]Zhouyuan Huo, Xue Jiang, Heng Huang:
Asynchronous Dual Free Stochastic Dual Coordinate Ascent for Distributed Data Mining. ICDM 2018: 167-176 - [c12]Bin Gu, Zhouyuan Huo, Cheng Deng, Heng Huang:
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines. ICML 2018: 1807-1816 - [c11]Zhouyuan Huo, Bin Gu, Qian Yang, Heng Huang:
Decoupled Parallel Backpropagation with Convergence Guarantee. ICML 2018: 2103-2111 - [c10]Zhouyuan Huo, Bin Gu, Heng Huang:
Training Neural Networks Using Features Replay. NeurIPS 2018: 6660-6669 - [c9]Zhouyuan Huo, Dinggang Shen, Heng Huang:
Genotype-Phenotype association study via new multi-task learning model. PSB 2018: 353-364 - [i10]Zhouyuan Huo, Bin Gu, Qian Yang, Heng Huang:
Decoupled Parallel Backpropagation with Convergence Guarantee. CoRR abs/1804.10574 (2018) - [i9]Zhouyuan Huo, Bin Gu, Heng Huang:
Training Neural Networks Using Features Replay. CoRR abs/1807.04511 (2018) - [i8]Liang Yang, Hao Jiang, Jizhong Xiao, Zhouyuan Huo:
Ego-Downward and Ambient Video based Person Location Association. CoRR abs/1812.00477 (2018) - 2017
- [c8]Zhouyuan Huo, Heng Huang:
Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization. AAAI 2017: 2043-2049 - [c7]Zhouyuan Huo, Shangqian Gao, Weidong Cai, Heng Huang:
Video Recovery via Learning Variation and Consistency of Images. AAAI 2017: 4082-4088 - [c6]Feiping Nie, Zhouyuan Huo, Heng Huang:
Joint Capped Norms Minimization for Robust Matrix Recovery. IJCAI 2017: 2557-2563 - [c5]Jie Xu, Xianglong Liu, Zhouyuan Huo, Cheng Deng, Feiping Nie, Heng Huang:
Multi-Class Support Vector Machine via Maximizing Multi-Class Margins. IJCAI 2017: 3154-3160 - [i7]Zhouyuan Huo, Bin Gu, Heng Huang:
Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization. CoRR abs/1711.03937 (2017) - 2016
- [c4]Zhouyuan Huo, Ji Liu, Heng Huang:
Optimal Discrete Matrix Completion. AAAI 2016: 1687-1693 - [c3]Dijun Luo, Zhouyuan Huo, Yang Wang, Andrew J. Saykin, Li Shen, Heng Huang:
New Probabilistic Multi-graph Decomposition Model to Identify Consistent Human Brain Network Modules. ICDM 2016: 301-310 - [c2]Zhouyuan Huo, Feiping Nie, Heng Huang:
Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm. KDD 2016: 1605-1614 - [c1]Zhouyuan Huo, Dinggang Shen, Heng Huang:
New Multi-task Learning Model to Predict Alzheimer's Disease Cognitive Assessment. MICCAI (1) 2016: 317-325 - [i6]Zhouyuan Huo, Heng Huang:
Asynchronous Stochastic Gradient Descent with Variance Reduction for Non-Convex Optimization. CoRR abs/1604.03584 (2016) - [i5]Zhouyuan Huo, Heng Huang:
Distributed Asynchronous Stochastic Dual Coordinate Ascent without Duality. CoRR abs/1605.09066 (2016) - [i4]Zhouyuan Huo, Bin Gu, Heng Huang:
Decoupled Asynchronous Proximal Stochastic Gradient Descent with Variance Reduction. CoRR abs/1609.06804 (2016) - [i3]Bin Gu, Zhouyuan Huo, Heng Huang:
Asynchronous Doubly Stochastic Proximal Optimization with Variance Reduction. CoRR abs/1610.09447 (2016) - [i2]Bin Gu, Zhouyuan Huo, Heng Huang:
Zeroth-order Asynchronous Doubly Stochastic Algorithm with Variance Reduction. CoRR abs/1612.01425 (2016) - [i1]Bin Gu, Zhouyuan Huo, Heng Huang:
Inexact Proximal Gradient Methods for Non-convex and Non-smooth Optimization. CoRR abs/1612.06003 (2016)
Coauthor Index
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