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Hui Guan 0001
Person information
- affiliation: University of Massachusetts Amherst, USA
- affiliation (former): North Carolina State University, Raleigh, USA
Other persons with the same name
- Hui Guan — disambiguation page
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2020 – today
- 2024
- [c28]Sohaib Ahmad
, Hui Guan
, Brian D. Friedman
, Thomas Williams
, Ramesh K. Sitaraman
, Thomas Y. C. Woo:
Proteus: A High-Throughput Inference-Serving System with Accuracy Scaling. ASPLOS (1) 2024: 318-334 - [c27]Qizheng Yang
, Tianyi Yang
, Mingcan Xiang
, Lijun Zhang
, Haoliang Wang
, Marco Serafini
, Hui Guan
:
GMorph: Accelerating Multi-DNN Inference via Model Fusion. EuroSys 2024: 505-523 - [c26]Sohaib Ahmad, Hui Guan, Ramesh K. Sitaraman:
Loki: A System for Serving ML Inference Pipelines with Hardware and Accuracy Scaling. HPDC 2024: 267-280 - [c25]Mohammad Mehdi Rastikerdar
, Jin Huang
, Shiwei Fang
, Hui Guan
, Deepak Ganesan
:
CACTUS: Dynamically Switchable Context-aware micro-Classifiers for Efficient IoT Inference. MobiSys 2024: 505-518 - [i25]Lijun Zhang, Xiao Liu, Antoni Viros Martin, Cindy Xiong Bearfield, Yuriy Brun, Hui Guan:
Robust Image Watermarking using Stable Diffusion. CoRR abs/2401.04247 (2024) - [i24]Juelin Liu, Sandeep Polisetty, Hui Guan, Marco Serafini:
GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs. CoRR abs/2403.01050 (2024) - [i23]Kunjal Panchal, Nisarg Parikh, Sunav Choudhary, Lijun Zhang, Yuriy Brun, Hui Guan:
Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. CoRR abs/2405.15551 (2024) - [i22]Saurabh Bajaj, Hui Guan, Marco Serafini:
Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. CoRR abs/2406.00552 (2024) - [i21]Hanmei Yang, Jin Zhou, Yao Fu, Xiaoqun Wang, Ramine Roane, Hui Guan, Tongping Liu:
ProTrain: Efficient LLM Training via Memory-Aware Techniques. CoRR abs/2406.08334 (2024) - [i20]Sohaib Ahmad, Hui Guan, Ramesh K. Sitaraman:
Loki: A System for Serving ML Inference Pipelines with Hardware and Accuracy Scaling. CoRR abs/2407.03583 (2024) - 2023
- [j5]Lijun Zhang
, Qizheng Yang
, Xiao Liu, Hui Guan:
An Alternative Hard-Parameter Sharing Paradigm for Multi-Domain Learning. IEEE Access 11: 10440-10452 (2023) - [c24]Juelin Liu, Sandeep Polisetty, Hui Guan, Marco Serafini:
GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs. PACT 2023: 211-224 - [c23]Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon:
Automatically marginalized MCMC in probabilistic programming. ICML 2023: 18301-18318 - [c22]Kunjal Panchal, Sunav Choudhary, Subrata Mitra, Koyel Mukherjee, Somdeb Sarkhel, Saayan Mitra, Hui Guan:
Flash: Concept Drift Adaptation in Federated Learning. ICML 2023: 26931-26962 - [c21]Hanmei Yang, Xin Zhao, Jin Zhou, Wei Wang
, Sandip Kundu
, Bo Wu, Hui Guan, Tongping Liu:
NUMAlloc: A Faster NUMA Memory Allocator. ISMM 2023: 97-110 - [c20]Jin Huang
, Hui Guan
, Deepak Ganesan
:
Re-thinking computation offload for efficient inference on IoT devices with duty-cycled radios. MobiCom 2023: 13:1-13:15 - [c19]Kunjal Panchal, Sunav Choudhary, Nisarg Parikh, Lijun Zhang, Hui Guan:
Flow: Per-instance Personalized Federated Learning. NeurIPS 2023 - [i19]Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon:
Automatically Marginalized MCMC in Probabilistic Programming. CoRR abs/2302.00564 (2023) - [i18]Sandeep Polisetty, Juelin Liu, Kobi Falus, Yi Ren Fung, Seung-Hwan Lim, Hui Guan, Marco Serafini:
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism. CoRR abs/2303.13775 (2023) - [i17]Siddhant Garg, Lijun Zhang, Hui Guan:
Structured Pruning for Multi-Task Deep Neural Networks. CoRR abs/2304.06840 (2023) - [i16]Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan:
Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. CoRR abs/2305.12066 (2023) - [i15]Mohammad Mehdi Rastikerdar, Jin Huang, Shiwei Fang
, Hui Guan, Deepak Ganesan:
Efficient IoT Inference via Context-Awareness. CoRR abs/2310.19112 (2023) - 2022
- [c18]Lijun Zhang, Xiao Liu, Hui Guan:
A Tree-Structured Multi-Task Model Recommender. AutoML 2022: 10/1-12 - [c17]Zifan Nan, Xipeng Shen, Hui Guan:
Enabling Near Real-Time NLU-Driven Natural Language Programming through Dynamic Grammar Graph-Based Translation. CGO 2022: 278-289 - [c16]Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan:
Rethinking Hard-Parameter Sharing in Multi-Domain Learning. ICME 2022: 1-6 - [c15]Lijun Zhang, Xiao Liu, Hui Guan:
AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning. NeurIPS 2022 - [i14]Lijun Zhang, Xiao Liu, Hui Guan:
A Tree-Structured Multi-Task Model Recommender. CoRR abs/2203.05092 (2022) - [i13]Yili Shen, Jiaxu Yan, Cheng-Wei Ju, Jun Yi, Zhou Lin, Hui Guan:
Improving Subgraph Representation Learning via Multi-View Augmentation. CoRR abs/2205.13038 (2022) - [i12]Xiao Liu, Lijun Zhang, Hui Guan:
Break the Wall Between Homophily and Heterophily for Graph Representation Learning. CoRR abs/2210.05382 (2022) - [i11]Kunjal Panchal, Sunav Choudhary
, Hui Guan:
Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing. CoRR abs/2211.15281 (2022) - 2021
- [j4]Hui Guan, Shaoshan Liu, Xiaolong Ma, Wei Niu
, Bin Ren, Xipeng Shen
, Yanzhi Wang, Pu Zhao
:
CoCoPIE: enabling real-time AI on off-the-shelf mobile devices via compression-compilation co-design. Commun. ACM 64(6): 62-68 (2021) - [j3]Lijun Zhang
, Hui Guan
, Yufei Ding, Xipeng Shen
, Hamid Krim:
Reuse-centric k-means configuration. Inf. Syst. 100: 101787 (2021) - [j2]Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Song, Dingwen Tao
:
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression. Proc. VLDB Endow. 15(4): 886-899 (2021) - [j1]Hui Guan
, Xipeng Shen
, Hamid Krim
:
An Automatic Synthesizer of Advising Tools for High Performance Computing. IEEE Trans. Parallel Distributed Syst. 32(2): 330-341 (2021) - [c14]Zifan Nan, Hui Guan, Xipeng Shen, Chunhua Liao:
Deep NLP-based co-evolvement for synthesizing code analysis from natural language. CC 2021: 141-152 - [c13]Hui Guan, Umana Chaudhary, Yuanchao Xu
, Lin Ning, Lijun Zhang, Xipeng Shen
:
Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. ICDM 2021: 1078-1083 - [c12]Xin Zhao, Jin Zhou, Hui Guan, Wei Wang
, Xu Liu, Tongping Liu:
NumaPerf: predictive NUMA profiling. ICS 2021: 52-62 - [c11]Shaurya Patel, Tongping Liu, Hui Guan:
FreeLunch: Compression-based GPU Memory Management for Convolutional Neural Networks. MCHPC@SC 2021: 1-8 - [i10]Xin Zhao, Jin Zhou, Hui Guan, Wei Wang, Xu Liu, Tongping Liu:
NumaPerf: Predictive and Full NUMA Profiling. CoRR abs/2102.05204 (2021) - [i9]Marco Serafini, Hui Guan:
Scalable Graph Neural Network Training: The Case for Sampling. CoRR abs/2105.02315 (2021) - [i8]Lijun Zhang, Qizheng Yang, Xiao Liu, Hui Guan:
Rethinking Hard-Parameter Sharing in Multi-Task Learning. CoRR abs/2107.11359 (2021) - [i7]Lijun Zhang, Xiao Liu, Hui Guan:
AutoMTL: A Programming Framework for Automated Multi-Task Learning. CoRR abs/2110.13076 (2021) - [i6]Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao:
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression. CoRR abs/2111.09562 (2021) - [i5]Yuezhou Sun, Wenlong Zhao, Lijun Zhang, Xiao Liu, Hui Guan, Matei Zaharia:
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression. CoRR abs/2111.10320 (2021) - 2020
- [c10]Hui Guan, Laxmikant Kishor Mokadam, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton:
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. MLSys 2020 - [c9]Zifan Nan, Hui Guan, Xipeng Shen:
HISyn: human learning-inspired natural language programming. ESEC/SIGSOFT FSE 2020: 75-86 - [i4]Lijun Zhang, Xiao Liu, Erik G. Learned-Miller, Hui Guan:
SID-NISM: A Self-supervised Low-light Image Enhancement Framework. CoRR abs/2012.08707 (2020)
2010 – 2019
- 2019
- [c8]Lin Ning
, Hui Guan, Xipeng Shen
:
Adaptive Deep Reuse: Accelerating CNN Training on the Fly. ICDE 2019: 1538-1549 - [c7]Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim:
In-Place Zero-Space Memory Protection for CNN. NeurIPS 2019: 5735-5744 - [c6]Hui Guan, Xipeng Shen
, Seung-Hwan Lim:
Wootz: a compiler-based framework for fast CNN pruning via composability. PLDI 2019: 717-730 - [i3]Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim:
In-Place Zero-Space Memory Protection for CNN. CoRR abs/1910.14479 (2019) - [i2]Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen:
Post-Training 4-bit Quantization on Embedding Tables. CoRR abs/1911.02079 (2019) - 2018
- [c5]Hui Guan, Yufei Ding, Xipeng Shen
, Hamid Krim:
Reuse-Centric K-Means Configuration. ICDE 2018: 1224-1227 - [c4]Randall Pittman, Hui Guan, Xipeng Shen, Seung-Hwan Lim, Robert M. Patton:
Exploring flexible communications for streamlining DNN ensemble training pipelines. SC 2018: 64:1-64:12 - 2017
- [c3]Yufei Ding, Lin Ning
, Hui Guan, Xipeng Shen
:
Generalizations of the theory and deployment of triangular inequality for compiler-based strength reduction. PLDI 2017: 33-48 - [c2]Hui Guan, Xipeng Shen
, Hamid Krim:
Egeria: a framework for automatic synthesis of HPC advising tools through multi-layered natural language processing. SC 2017: 10 - [i1]Hui Guan, Thanos Gentimis, Hamid Krim, James Keiser:
First Study on Data Readiness Level. CoRR abs/1702.02107 (2017) - 2016
- [c1]Hui Guan, Wen Tang, Hamid Krim, James Keiser, Andrew J. Rindos, Radmila Sazdanovic
:
A topological collapse for document summarization. SPAWC 2016: 1-5
Coauthor Index
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