Binhang Yuan

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 53

Top Topics

Machine Learning

Change Point Detection

Relational Algebra

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

Publications

Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cedric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang
Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. VLDB J. 33 (5) (2024)
Lixi Zhou, Qi Lin, Kanchan Chowdhury, Saif Masood, Alexandre E. Eichenberger, Hong Min, Alexander Sim, Jie Wang, Yida Wang, Kesheng Wu, Binhang Yuan, Jia Zou
Serving Deep Learning Models from Relational Databases. EDBT (2024)
Suyi Li, Hanfeng Lu, Tianyuan Wu, Minchen Yu, Qizhen Weng, Xusheng Chen, Yizhou Shan, Binhang Yuan, Wei Wang
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference. CoRR (2024)
Jinwei Yao, Kaiqi Chen, Kexun Zhang, Jiaxuan You, Binhang Yuan, Zeke Wang, Tao Lin
DeFT: Flash Tree-attention with IO-Awareness for Efficient Tree-search-based LLM Inference. CoRR (2024)
Changyue Liao, Mo Sun, Zihan Yang, Kaiqi Chen, Binhang Yuan, Fei Wu, Zeke Wang
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU. CoRR (2024)
Lujia Zhang, Hanzhe Cui, Yurong Song, Chenyue Li, Binhang Yuan, Mengqian Lu
On the Opportunities of (Re)-Exploring Atmospheric Science by Foundation Models: A Case Study. CoRR (2024)
Tianyi Bai, Hao Liang, Binwang Wan, Ling Yang, Bozhou Li, Yifan Wang, Bin Cui, Conghui He, Binhang Yuan, Wentao Zhang
A Survey of Multimodal Large Language Model from A Data-centric Perspective. CoRR (2024)
Xinrun Du, Zhouliang Yu, Songyang Gao, Ding Pan, Yuyang Cheng, Ziyang Ma, Ruibin Yuan, Xingwei Qu, Jiaheng Liu, Tianyu Zheng, Xinchen Luo, Guorui Zhou, Binhang Yuan, Wenhu Chen, Jie Fu, Ge Zhang
Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model. CoRR (2024)
Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML (2023)
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR (2023)
Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Ré, Ce Zhang
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks. ICML (2023)
Alexandre E. Eichenberger, Qi Lin, Saif Masood, Hong Min, Alexander Sim, Jie Wang, Yida Wang, Kesheng Wu, Binhang Yuan, Lixi Zhou, Jia Zou
Serving Deep Learning Model in Relational Databases. CoRR (2023)
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML (2023)
Youhe Jiang, Ran Yan, Xiaozhe Yao, Beidi Chen, Binhang Yuan
HexGen: Generative Inference of Foundation Model over Heterogeneous Decentralized Environment. CoRR (2023)
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023)
Yuxin Tang, Zhimin Ding, Dimitrije Jankov, Binhang Yuan, Daniel Bourgeois, Chris Jermaine
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning. ICML (2023)
Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR (2023)
Lin Lu, Chenxi Dai, Wangcheng Tao, Binhang Yuan, Yanan Sun, Pan Zhou
Exploring the Robustness of Decentralized Training for Large Language Models. CoRR (2023)
Yuxin Tang, Zhimin Ding, Dimitrije Jankov, Binhang Yuan, Daniel Bourgeois, Chris Jermaine
Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning. CoRR (2023)
Rui Pan, Yiming Lei, Jialong Li, Zhiqiang Xie, Binhang Yuan, Yiting Xia
Efficient flow scheduling in distributed deep learning training with echelon formation. HotNets (2022)
Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
Decentralized Training of Foundation Models in Heterogeneous Environments. NeurIPS (2022)
Binhang Yuan, Cameron R. Wolfe, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine
Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training. Proc. VLDB Endow. 15 (8) (2022)
Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang
Decentralized Training of Foundation Models in Heterogeneous Environments. CoRR (2022)
Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. KDD (2022)
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
Holistic Evaluation of Language Models. CoRR (2022)
Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. NeurIPS (2022)
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference (2022)
Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang
Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. CoRR (2022)
Zijian Ding, Guijin Wang, Huazhong Yang, Ping Zhang, Dapeng Fu, Zhen Yang, Xinkang Wang, Xia Wang, Zhourui Xia, Chiming Zhang, Wenjie Cai, Binhang Yuan, Dongya Jia, Bo Chen, Chengbin Huang, Jing Zhang, Yi Li, Shan Yang, Runnan He
A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram. Medical Biol. Eng. Comput. 60 (1) (2022)
Huaqing Jin, Guosheng Yin, Binhang Yuan, Fei Jiang
Bayesian Hierarchical Model for Change Point Detection in Multivariate Sequences. Technometrics 64 (2) (2022)
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang
Stochastic Gradient Descent without Full Data Shuffle. CoRR (2022)
Dimitrije Jankov, Binhang Yuan, Shangyu Luo, Chris Jermaine
Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees. Proc. VLDB Endow. 14 (7) (2021)
Jia Zou, Amitabh Das, Pratik Barhate, Arun Iyengar, Binhang Yuan, Dimitrije Jankov, Chris Jermaine
Lachesis: Automated Partitioning for UDF-Centric Analytics. Proc. VLDB Endow. 14 (8) (2021)
Binhang Yuan, Dimitrije Jankov, Jia Zou, Yuxin Tang, Daniel Bourgeois, Chris Jermaine
Tensor Relational Algebra for Distributed Machine Learning System Design. Proc. VLDB Endow. 14 (8) (2021)
Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
BAGUA: Scaling up Distributed Learning with System Relaxations. Proc. VLDB Endow. 15 (4) (2021)
Chengbin Huang, Weiting Chen, Mingsong Chen, Binhang Yuan
A Feature Fusion Framework and Its Application to Automatic Seizure Detection. IEEE Signal Process. Lett. 28 (2021)
Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
BAGUA: Scaling up Distributed Learning with System Relaxations. CoRR (2021)
Xiangru Lian, Binhang Yuan, Xuefeng Zhu, Yulong Wang, Yongjun He, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu
Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. CoRR (2021)
Shangyu Luo, Dimitrije Jankov, Binhang Yuan, Chris Jermaine
Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra. SIGMOD Conference (2021)
Binhang Yuan, Song Ge, Wenhui Xing
A Federated Learning Framework for Healthcare IoT devices. CoRR (2020)
Dimitrije Jankov, Shangyu Luo, Binhang Yuan, Zhuhua Cai, Jia Zou, Chris Jermaine, Zekai J. Gao
Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning. SIGMOD Rec. 49 (1) (2020)
Jia Zou, Pratik Barhate, Amitabh Das, Arun Iyengar, Binhang Yuan, Dimitrije Jankov, Chris Jermaine
Lachesis: Automated Generation of Persistent Partitionings for Big Data Applications. CoRR (2020)
Binhang Yuan, Dimitrije Jankov, Jia Zou, Yuxin Tang, Daniel Bourgeois, Chris Jermaine
Tensor Relational Algebra for Machine Learning System Design. CoRR (2020)
Dimitrije Jankov, Shangyu Luo, Binhang Yuan, Zhuhua Cai, Jia Zou, Chris Jermaine, Zekai J. Gao
Declarative Recursive Computation on an RDBMS. Proc. VLDB Endow. 12 (7) (2019)
Binhang Yuan, Anastasios Kyrillidis, Christopher M. Jermaine
Distributed Learning of Deep Neural Networks using Independent Subnet Training. CoRR (2019)
Binhang Yuan, Chen Wang, Fei Jiang, Mingsheng Long, Philip S. Yu, Yuan Liu
WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection. CoRR (2019)
Binhang Yuan, Wenhui Xing
Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks. MLMECH/CVII-STENT@MICCAI (2019)
Binhang Yuan, Wenhui Xing
Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks. CoRR (2019)
Dimitrije Jankov, Shangyu Luo, Binhang Yuan, Zhuhua Cai, Jia Zou, Chris Jermaine, Zekai J. Gao
Declarative Recursive Computation on an RDBMS, or, Why You Should Use a Database For Distributed Machine Learning. CoRR (2019)
Jia Zou, R. Matthew Barnett, Tania Lorido-Botran, Shangyu Luo, Carlos Monroy, Sourav Sikdar, Kia Teymourian, Binhang Yuan, Chris Jermaine
PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development. SIGMOD Conference (2018)
Binhang Yuan, Vijayaraghavan Murali, Christopher M. Jermaine
Abridging source code. Proc. ACM Program. Lang. 1 (OOPSLA) (2017)
Jia Zou, R. Matthew Barnett, Tania Lorido-Botran, Shangyu Luo, Carlos Monroy, Sourav Sikdar, Kia Teymourian, Binhang Yuan, Chris Jermaine
PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development. CoRR (2017)
Binhang Yuan, Ronald N. Goldman, Eric Wang, Olushola Olorunnipa, David Khechoyan
Generating a 3D Normative Infant Cranial Model. ICCS (2016)
Bo Yan, Binhang Yuan, Bo Yang
Effective Video Retargeting With Jittery Assessment. IEEE Trans. Multim. 16 (1) (2014)