| 2025 | ICLR | Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning. | Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Xiao Cheng, Jun Huan, Haoyu Wang, Jing Gao |
| 2025 | ICLR | Enhancing Language Model Agents using Diversity of Thoughts. | Vijay Lingam, Behrooz Omidvar-Tehrani, Sujay Sanghavi, Gaurav Gupta, Sayan Ghosh, Linbo Liu, Jun Huan, Anoop Deoras |
| 2025 | KDD | KDD 2025 - AI Reasoning Day. | Jun Huan, Xiangyu Zhang, Ye Xing, Wee Hyong Tok, Ruzica Piskac |
| 2025 | KDD | The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Yuxuan Liang, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2024 | KDD | Reasoning and Planning with Large Language Models in Code Development. | Hao Ding, Ziwei Fan, Ingo Ghring, Gaurav Gupta, Wooseok Ha, Jun Huan, Linbo Liu, Behrooz Omidvar-Tehrani, Shiqi Wang, Hao Zhou |
| 2024 | KDD | Inference Optimization of Foundation Models on AI Accelerators. | Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kbler, Jiaji Huang, Matthus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis |
| 2024 | KDD | The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2024 | KDD | NL2Code-Reasoning and Planning with LLMs for Code Development. | Ye Xing, Jun Huan, Wee Hyong Tok, Cong Shen, Johannes Gehrke, Katherine Lin, Arjun Guha, Omer Tripp, Murali Krishna Ramanathan |
| 2023 | ICML | Fast Federated Machine Unlearning with Nonlinear Functional Theory. | Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan |
| 2023 | KDD | Training Large-scale Foundation Models on Emerging AI Chips. | Aashiq Muhamed, Christian Bock, Rahul Solanki, Youngsuk Park, Yida Wang, Jun Huan |
| 2023 | KDD | The 9th SIGKDD International Workshop on Mining and Learning from Time Series. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Yuriy Nevmyvaka |
| 2022 | ICASSP | Parameter-Free Style Projection for Arbitrary Image Style Transfer. | Siyu Huang, Haoyi Xiong, Tianyang Wang, Bihan Wen, Qingzhong Wang, Zeyu Chen, Jun Huan, Dejing Dou |
| 2022 | KDD | The Sixth International Workshop on Automation in Machine Learning. | Patrick Koch, Brett Wujek, Jun Liu, Jun Huan, Tao Wang |
| 2022 | KDD | 8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. | Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka |
| 2021 | ICCV | Semi-Supervised Active Learning with Temporal Output Discrepancy. | Siyu Huang, Tianyang Wang, Haoyi Xiong, Jun Huan, Dejing Dou |
| 2020 | AAAI | Ultrafast Photorealistic Style Transfer via Neural Architecture Search. | Jie An, Haoyi Xiong, Jun Huan, Jiebo Luo |
| 2020 | ICDM | Rethinking Local Community Detection: Query Nodes Replacement. | Yuchen Bian, Jun Huan, Dejing Dou, Xiang Zhang |
| 2020 | ICLR | FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary. | Yingzhen Yang, Jiahui Yu, Nebojsa Jojic, Jun Huan, Thomas S. Huang |
| 2020 | ICML | On the Noisy Gradient Descent that Generalizes as SGD. | Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu |
| 2020 | IJCAI | Generating Person Images with Appearance-aware Pose Stylizer. | Siyu Huang, Haoyi Xiong, Zhi-Qi Cheng, Qingzhong Wang, Xingran Zhou, Bihan Wen, Jun Huan, Dejing Dou |
| 2020 | KDD | Local Community Detection in Multiple Networks. | Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang |
| 2019 | AAAI | Understanding Actors and Evaluating Personae with Gaussian Embeddings. | Hannah Kim, Denys Katerenchuk, Daniel Billet, Jun Huan, Haesun Park, Boyang Li |
| 2019 | AAAI | SpHMC: Spectral Hamiltonian Monte Carlo. | Haoyi Xiong, Kafeng Wang, Jiang Bian, Zhanxing Zhu, Cheng-Zhong Xu, Zhishan Guo, Jun Huan |
| 2019 | ICDM | Towards Making Deep Transfer Learning Never Hurt. | Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan |
| 2019 | ICLR | Delta: Deep Learning Transfer using Feature Map with Attention for Convolutional Networks. | Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao, Liping Liu, Jun Huan |
| 2019 | ICTAI | Rethink Gaussian Denoising Prior for Real-World Image Denoising. | Tianyang Wang, Jun Huan, Bo Li, Kaoning Hu |
| 2019 | PRICAI | Simple Is Better: A Global Semantic Consistency Based End-to-End Framework for Effective Zero-Shot Learning. | Fan Wu, Shuigeng Zhou, Kang Wang, Yi Xu, Jihong Guan, Jun Huan |
| 2019 | WACV | Instance-Based Deep Transfer Learning. | Tianyang Wang, Jun Huan, Michelle Zhu |
| 2018 | CIKM | Interactions Modeling in Multi-Task Multi-View Learning with Consistent Task Diversity. | Xiaoli Li, Jun Huan |
| 2018 | ICTAI | Data Dropout: Optimizing Training Data for Convolutional Neural Networks. | Tianyang Wang, Jun Huan, Bo Li |
| 2017 | KDD | Constructivism Learning: A Learning Paradigm for Transparent Predictive Analytics. | Xiaoli Li, Jun Huan |
| 2017 | KDD | Sparse Compositional Local Metric Learning. | Joseph St. Amand, Jun Huan |
| 2016 | CIKM | aptMTVL: Nailing Interactions in Multi-Task Multi-View Multi-Label Learning using Adaptive-basis Multilinear Factor Analyzers. | Xiaoli Li, Jun Huan |
| 2016 | CIKM | Discriminative View Learning for Single View Co-Training. | Joseph St. Amand, Jun Huan |
| 2016 | DCC | CS2A: A Compressed Suffix Array-Based Method for Short Read Alignment. | Hongwei Huo, Zhigang Sun, Shuangjiang Li, Jeffrey Scott Vitter, Xinkun Wang, Qiang Yu, Jun Huan |
| 2016 | ICPR | A PAC bound for joint matrix completion based on Partially Collective Matrix Factorization. | Chao Lan, Xiaoli Li, Yujie Deng, Joseph St. Amand, Jun Huan |
| 2016 | IJCNN | Co-regularized least square regression for multi-view multi-class classification. | Chao Lan, Yujie Deng, Xiaoli Li, Jun Huan |
| 2016 | IJCNN | A disagreement-based active matrix completion approach with provable guarantee. | Chao Lan, Yujie Deng, Jun Huan |
| 2016 | ISAIM | Partial Collective Matrix Factorization and its PAC Bound. | Chao Lan, Xiaoli Li, Yujie Deng, Jun Huan |
| 2016 | UAI | Towards a Theoretical Understanding of Negative Transfer in Collective Matrix Factorization. | Chao Lan, Jianxin Wang, Jun Huan |
| 2015 | CIKM | Learning Task Grouping using Supervised Task Space Partitioning in Lifelong Multitask Learning. | Meenakshi Mishra, Jun Huan |
| 2015 | KDD | Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning. | Chao Lan, Jun Huan |
| 2014 | CIKM | Automatic Social Circle Detection Using Multi-View Clustering. | Yuhao Yang, Chao Lan, Xiaoli Li, Bo Luo, Jun Huan |
| 2013 | ICDM | Multitask Learning with Feature Selection for Groups of Related Tasks. | Meenakshi Mishra, Jun Huan |
| 2012 | CIKM | Non-stationary bayesian networks based on perfect simulation. | Yi Jia, Wenrong Zeng, Jun Huan |
| 2012 | CIKM | CoNet: feature generation for multi-view semi-supervised learning with partially observed views. | Brian Quanz, Jun Huan |
| 2012 | DASFAA | Semi-supervised Clustering of Graph Objects: A Subgraph Mining Approach. | Xin Huang, Hong Cheng, Jiong Yang, Jeffrey Xu Yu, Hongliang Fei, Jun Huan |
| 2012 | ICDM | When Additional Views are Not Free: Active View Completion for Multi-view Semi-Supervised Learning. | Brian Quanz, Jun Huan |
| 2012 | KDD | Biomedical text categorization with concept graph representations using a controlled vocabulary. | Meenakshi Mishra, Jun Huan, Said Bleik, Min Song |
| 2012 | KDD | Inductive multi-task learning with multiple view data. | Jintao Zhang, Jun Huan |
| 2011 | CIKM | Content based social behavior prediction: a multi-task learning approach. | Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo, Jun Huan |
| 2011 | ICDE | Knowledge transfer with low-quality data: A feature extraction issue. | Brian Quanz, Jun Huan, Meenakshi Mishra |
| 2011 | ICDM | Structured Feature Selection and Task Relationship Inference for Multi-task Learning. | Hongliang Fei, Jun Huan |
| 2011 | KDD | Anomaly localization for network data streams with graph joint sparse PCA. | Ruoyi Jiang, Hongliang Fei, Jun Huan |
| 2010 | CIKM | Regularization and feature selection for networked features. | Hongliang Fei, Brian Quanz, Jun Huan |
| 2010 | ICDM | Knowledge Discovery in Academic Drug Discovery Programs: Opportunities and Challenges. | Jun Huan |
| 2010 | KDD | Boosting with structure information in the functional space: an application to graph classification. | Hongliang Fei, Jun Huan |
| 2009 | CIKM | L2 norm regularized feature kernel regression for graph data. | Hongliang Fei, Jun Huan |
| 2009 | CIKM | Large margin transductive transfer learning. | Brian Quanz, Jun Huan |
| 2009 | EDBT | G-hash: towards fast kernel-based similarity search in large graph databases. | Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald H. Lushington |
| 2009 | ICCCN | Anomaly Detection with Sensor Data for Distributed Security. | Brian Quanz, Hongliang Fei, Jun Huan, Joseph B. Evans, Victor Frost, Gary J. Minden, Daniel D. Deavours, Leon S. Searl, Daniel DePardo, Martin Kuehnhausen, Daniel Fokum, Matt Zeets, Angela Oguna |
| 2009 | ICDM | GLSVM: Integrating Structured Feature Selection and Large Margin Classification. | Hongliang Fei, Brian Quanz, Jun Huan |
| 2009 | ICDM | Feature Selection in the Tensor Product Feature Space. | Aaron M. Smalter, Jun Huan, Gerald H. Lushington |
| 2009 | SDM | Aligned Graph Classification with Regularized Logistic Regression. | Brian Quanz, Jun Huan |
| 2008 | APBC | Chemical Compound Classification with Automatically Mined Structure Patterns. | Aaron M. Smalter, Jun Huan, Gerald H. Lushington |
| 2008 | BIBE | Structure feature selection for chemical compound classification. | Hongliang Fei, Jun Huan |
| 2008 | BIBE | GPM: A graph pattern matching kernel with diffusion for chemical compound classification. | Aaron M. Smalter, Jun Huan, Gerald H. Lushington |
| 2008 | CIKM | Structure feature selection for graph classification. | Hongliang Fei, Jun Huan |
| 2008 | CIKM | Biological pathways as features for microarray data classification. | Brian Quanz, Meeyoung Park, Jun Huan |
| 2007 | ICDE | Graph Database Indexing Using Structured Graph Decomposition. | David W. Williams, Jun Huan, Wei Wang |
| 2007 | SDM | On Demand Phenotype Ranking through Subspace Clustering. | Xiang Zhang, Wei Wang, Jun Huan |
| 2007 | SSDBM | Mining RNA Tertiary Motifs with Structure Graphs. | Xueyi Wang, Jun Huan, Jack Snoeyink, Wei Wang |
| 2004 | KDD | SPIN: mining maximal frequent subgraphs from graph databases. | Jun Huan, Wei Wang, Jan F. Prins, Jiong Yang |
| 2004 | PSB | Accurate Classification of Protein Structural Families Using Coherent Subgraph Analysis. | Jun Huan, Wei Wang, Anglina Washington, Jan F. Prins, Ruchir Shah, Alexander Tropsha |
| 2004 | RECOMB | Mining protein family specific residue packing patterns from protein structure graphs. | Jun Huan, Wei Wang, Deepak Bandyopadhyay, Jack Snoeyink, Jan F. Prins, Alexander Tropsha |
| 2003 | ICDM | Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism. | Jun Huan, Wei Wang, Jan F. Prins |