A topological collapse for document summarization. - Hui Guan 001; Wen Tang; Hamid Krim; James Keiser; Andrew J. Rindos; Radmila Sazdanovic (SPAWC, 2016)

Generalizations of the theory and deployment of triangular inequality for compiler-based strength reduction. - Yufei Ding 001; Lin Ning 001; Hui Guan 001; Xipeng Shen (PLDI, 2017)

Egeria: a framework for automatic synthesis of HPC advising tools through multi-layered natural language processing. - Hui Guan 001; Xipeng Shen; Hamid Krim (SC, 2017)

First Study on Data Readiness Level. - Hui Guan 001; Thanos Gentimis; Hamid Krim; James Keiser (CoRR, 2017)

Reuse-Centric K-Means Configuration. - Hui Guan 001; Yufei Ding 001; Xipeng Shen; Hamid Krim (ICDE, 2018)

Exploring flexible communications for streamlining DNN ensemble training pipelines. - Randall Pittman; Hui Guan 001; Xipeng Shen; Seung-Hwan Lim; Robert M. Patton (SC, 2018)

Adaptive Deep Reuse: Accelerating CNN Training on the Fly. - Lin Ning 001; Hui Guan 001; Xipeng Shen (ICDE, 2019)

In-Place Zero-Space Memory Protection for CNN. - Hui Guan 001; Lin Ning 001; Zhen Lin; Xipeng Shen; Huiyang Zhou; Seung-Hwan Lim (NeurIPS, 2019)

Wootz: a compiler-based framework for fast CNN pruning via composability. - Hui Guan 001; Xipeng Shen; Seung-Hwan Lim (PLDI, 2019)

Post-Training 4-bit Quantization on Embedding Tables. - Hui Guan 001; Andrey Malevich; Jiyan Yang; Jongsoo Park; Hector Yuen (CoRR, 2019)

FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. - Hui Guan 001; Laxmikant Kishor Mokadam; Xipeng Shen; Seung-Hwan Lim; Robert M. Patton (MLSys, 2020)

HISyn: human learning-inspired natural language programming. - Zifan Nan; Hui Guan 001; Xipeng Shen (ESEC/SIGSOFT FSE, 2020)

SID-NISM: A Self-supervised Low-light Image Enhancement Framework. - Lijun Zhang 005; Xiao Liu 030; Erik G. Learned-Miller; Hui Guan 001 (CoRR, 2020)

Deep NLP-based co-evolvement for synthesizing code analysis from natural language. - Zifan Nan; Hui Guan 001; Xipeng Shen; Chunhua Liao (CC, 2021)

Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. - Hui Guan 001; Umana Chaudhary; Yuanchao Xu 001; Lin Ning 001; Lijun Zhang 005; Xipeng Shen (ICDM, 2021)

NumaPerf: predictive NUMA profiling. - Xin Zhao; Jin Zhou; Hui Guan 001; Wei Wang 054; Xu Liu 001; Tongping Liu (ICS, 2021)

FreeLunch: Compression-based GPU Memory Management for Convolutional Neural Networks. - Shaurya Patel; Tongping Liu; Hui Guan 001 (MCHPC@SC, 2021)

CoCoPIE: enabling real-time AI on off-the-shelf mobile devices via compression-compilation co-design. - Hui Guan 001; Shaoshan Liu; Xiaolong Ma; Wei Niu 002; Bin Ren; Xipeng Shen; Yanzhi Wang; Pu Zhao 001 (Commun. ACM, 2021)

NumaPerf: Predictive and Full NUMA Profiling. - Xin Zhao; Jin Zhou; Hui Guan 001; Wei Wang 054; Xu Liu 001; Tongping Liu (CoRR, 2021)

Scalable Graph Neural Network Training: The Case for Sampling. - Marco Serafini; Hui Guan 001 (CoRR, 2021)

Rethinking Hard-Parameter Sharing in Multi-Task Learning. - Lijun Zhang 005; Qizheng Yang; Xiao Liu 030; Hui Guan 001 (CoRR, 2021)

AutoMTL: A Programming Framework for Automated Multi-Task Learning. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (CoRR, 2021)

Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression. - Yuezhou Sun; Wenlong Zhao 001; Lijun Zhang 005; Xiao Liu 030; Hui Guan 001; Matei Zaharia (CoRR, 2021)

Reuse-centric k-means configuration. - Lijun Zhang 005; Hui Guan 001; Yufei Ding 001; Xipeng Shen; Hamid Krim (Inf. Syst., 2021)

COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression. - Sian Jin; Chengming Zhang 006; Xintong Jiang; Yunhe Feng; Hui Guan 001; Guanpeng Li; Shuaiwen Song; Dingwen Tao (Proc. VLDB Endow., 2021)

An Automatic Synthesizer of Advising Tools for High Performance Computing. - Hui Guan 001; Xipeng Shen; Hamid Krim (IEEE Trans. Parallel Distributed Syst., 2021)

A Tree-Structured Multi-Task Model Recommender. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (AutoML, 2022)

Enabling Near Real-Time NLU-Driven Natural Language Programming through Dynamic Grammar Graph-Based Translation. - Zifan Nan; Xipeng Shen; Hui Guan 001 (CGO, 2022)

Rethinking Hard-Parameter Sharing in Multi-Domain Learning. - Lijun Zhang 005; Qizheng Yang; Xiao Liu 030; Hui Guan 001 (ICME, 2022)

AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (NeurIPS, 2022)

Improving Subgraph Representation Learning via Multi-View Augmentation. - Yili Shen; Jiaxu Yan; Cheng-Wei Ju; Jun Yi; Zhou Lin; Hui Guan 001 (CoRR, 2022)

Break the Wall Between Homophily and Heterophily for Graph Representation Learning. - Xiao Liu 030; Lijun Zhang 005; Hui Guan 001 (CoRR, 2022)

Flow: Per-Instance Personalized Federated Learning Through Dynamic Routing. - Kunjal Panchal; Sunav Choudhary; Hui Guan 001 (CoRR, 2022)

GraphMini: Accelerating Graph Pattern Matching Using Auxiliary Graphs. - Juelin Liu; Sandeep Polisetty; Hui Guan 001; Marco Serafini (PACT, 2023)

Automatically marginalized MCMC in probabilistic programming. - Jinlin Lai; Javier Burroni; Hui Guan 001; Daniel Sheldon (ICML, 2023)

Flash: Concept Drift Adaptation in Federated Learning. - Kunjal Panchal; Sunav Choudhary; Subrata Mitra; Koyel Mukherjee; Somdeb Sarkhel; Saayan Mitra; Hui Guan 001 (ICML, 2023)

NUMAlloc: A Faster NUMA Memory Allocator. - Hanmei Yang; Xin Zhao; Jin Zhou; Wei Wang 054; Sandip Kundu; Bo Wu 002; Hui Guan 001; Tongping Liu (ISMM, 2023)

Re-thinking computation offload for efficient inference on IoT devices with duty-cycled radios. - Jin Huang; Hui Guan 001; Deepak Ganesan (MobiCom, 2023)

Flow: Per-instance Personalized Federated Learning. - Kunjal Panchal; Sunav Choudhary; Nisarg Parikh; Lijun Zhang 005; Hui Guan 001 (NeurIPS, 2023)

An Alternative Hard-Parameter Sharing Paradigm for Multi-Domain Learning. - Lijun Zhang 005; Qizheng Yang; Xiao Liu 030; Hui Guan 001 (IEEE Access, 2023)

GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism. - Sandeep Polisetty; Juelin Liu; Kobi Falus; Yi Ren Fung 001; Seung-Hwan Lim; Hui Guan 001; Marco Serafini (CoRR, 2023)

Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. - Lijun Zhang 005; Xiao Liu 030; Kaleel Mahmood; Caiwen Ding; Hui Guan 001 (CoRR, 2023)

Efficient IoT Inference via Context-Awareness. - Mohammad Mehdi Rastikerdar; Jin Huang; Shiwei Fang; Hui Guan 001; Deepak Ganesan (CoRR, 2023)

Proteus: A High-Throughput Inference-Serving System with Accuracy Scaling. - Sohaib Ahmad; Hui Guan 001; Brian D. Friedman; Thomas Williams; Ramesh K. Sitaraman; Thomas Y. C. Woo (ASPLOS (1), 2024)

GMorph: Accelerating Multi-DNN Inference via Model Fusion. - Qizheng Yang; Tianyi Yang; Mingcan Xiang; Lijun Zhang 005; Haoliang Wang; Marco Serafini; Hui Guan 001 (EuroSys, 2024)

Loki: A System for Serving ML Inference Pipelines with Hardware and Accuracy Scaling. - Sohaib Ahmad; Hui Guan 001; Ramesh K. Sitaraman (HPDC, 2024)

Structured Pruning for Multi-Task Deep Neural Networks. - Siddhant Garg; Lijun Zhang 005; Hui Guan 001 (MIPR, 2024)

AdapMTL: Adaptive Pruning Framework for Multitask Learning Model. - Mingcan Xiang; Jiaxun Tang; Qizheng Yang; Hui Guan 001; Tongping Liu (ACM Multimedia, 2024)

CACTUS: Dynamically Switchable Context-aware micro-Classifiers for Efficient IoT Inference. - Mohammad Mehdi Rastikerdar; Jin Huang; Shiwei Fang; Hui Guan 001; Deepak Ganesan (MobiSys, 2024)

Thinking Forward: Memory-Efficient Federated Finetuning of Language Models. - Kunjal Panchal; Nisarg Parikh; Sunav Choudhary; Lijun Zhang 005; Yuriy Brun; Hui Guan 001 (NeurIPS, 2024)

Attack-Resilient Image Watermarking Using Stable Diffusion. - Lijun Zhang 005; Xiao Liu 030; Antoni Viros Martin; Cindy Xiong Bearfield; Yuriy Brun; Hui Guan 001 (NeurIPS, 2024)

Information-Enhanced Graph Neural Network for Transcending Homophily Barriers. - Xiao Liu 030; Lijun Zhang 005; Hui Guan 001 (IEEE Access, 2024)

Robust Image Watermarking using Stable Diffusion. - Lijun Zhang 005; Xiao Liu 030; Antoni Viros Martin; Cindy Xiong Bearfield; Yuriy Brun; Hui Guan 001 (CoRR, 2024)

Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. - Saurabh Bajaj; Hui Guan 001; Marco Serafini (CoRR, 2024)

ProTrain: Efficient LLM Training via Memory-Aware Techniques. - Hanmei Yang; Jin Zhou; Yao Fu; Xiaoqun Wang; Ramine Roane; Hui Guan 001; Tongping Liu (CoRR, 2024)

In-Situ Fine-Tuning of Wildlife Models in IoT-Enabled Camera Traps for Efficient Adaptation. - Mohammad Mehdi Rastikerdar; Jin Huang; Hui Guan 001; Deepak Ganesan (CoRR, 2024)

Understanding and Alleviating Memory Consumption in RLHF for LLMs. - Jin Zhou; Hanmei Yang; Steven (Jiaxun) Tang; Mingcan Xiang; Hui Guan 001; Tongping Liu (CoRR, 2024)

Integrating Graph Neural Networks and Many-Body Expansion Theory for Potential Energy Surfaces. - Siqi Chen; Zhiqiang Wang; Xianqi Deng; Yili Shen; Cheng-Wei Ju; Jun Yi; Lin Xiong; Guo Ling; Dieaa Alhmoud; Hui Guan 001; Zhou Lin (CoRR, 2024)

Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models. - Xiao Liu 030; Lijun Zhang 005; Deepak Ganesan; Hui Guan 001 (CoRR, 2024)

DiffServe: Efficiently Serving Text-to-Image Diffusion Models with Query-Aware Model Scaling. - Sohaib Ahmad; Qizheng Yang; Haoliang Wang; Ramesh K. Sitaraman; Hui Guan 001 (CoRR, 2024)

A Tree-Structured Multitask Model Architectures Recommendation System. - Lijun Zhang 005; Xiao Liu 030; Hui Guan 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. - Saurabh Bajaj; Hui Guan 001; Marco Serafini; Juelin Liu; Hojae Son (Proc. VLDB Endow., 2024)

An Empirical Study of Microscaling Formats for Low-Precision LLM Training. - Hanmei Yang; Summer Deng; Amit Nagpal; Maxim Naumov; Mohammad Janani; Tongping Liu; Hui Guan 001 (ARITH, 2025)

What Makes a Visualization Visually Complex? - Kylie Lin; Sean Sheng-tse Ru; David N. Rapp; Hui Guan 001; Cindy Xiong Bearfield (CHI Extended Abstracts, 2025)

Communication-Efficient Multi-Device Inference Acceleration for Transformer Models. - Xiao Liu 030; Lijun Zhang 005; Deepak Ganesan; Hui Guan 001 (CoRR, 2025)

The Cost of Avoiding Backpropagation. - Kunjal Panchal; Sunav Choudhary; Yuriy Brun; Hui Guan 001 (CoRR, 2025)

Adaptive Spiking with Plasticity for Energy Aware Neuromorphic Systems. - Eduardo Calle-Ortiz; Hui Guan 001; Deepak Ganesan; Phuc Nguyen (CoRR, 2025)