Publications

Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, YuQing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stark, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alan Aspuru-Guzik, Erik Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Lio, Rose Yu, Stephan Gunnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
[Paper] [GitHub] [Website]

Hongyi Ling, Zhimeng Jiang, Na Zou, Shuiwang Ji
Counterfactual Fairness on Graphs: Augmentations, Hidden Confounders, and Identifiability
Transactions on Machine Learning Research, 2025
[Paper] [Code]

Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arroyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
The 38th Conference on Neural Information Processing Systems (NeurIPS), x-x, 2024
[Paper] [Code]

Yu Zhang, Xiusi Chen, Bowen Jin, Sheng Wang, Shuiwang Ji, Wei Wang, Jiawei Han
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery
Conference on Empirical Methods in Natural Language Processing (EMNLP), 8783-8817, 2024
[Paper] [Project]

Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
International Conference on Machine Learning (ICML), 30042-30079, 2024 (Spotlight, 3.5% acceptance rate)
[Paper] [Code]

Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction
International Conference on Machine Learning (ICML), 55797-55813, 2024
[Paper] [Code]

Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji
Graph Structure Extrapolation for Out-of-Distribution Generalization
International Conference on Machine Learning (ICML), 27846-27874, 2024
[Paper] [Code]

Yue Huang, Lichao Sun, …, Xiner Li, …, Shuiwang Ji, …, Yue Zhao
TrustLLM: Trustworthiness in Large Language Models
International Conference on Machine Learning (ICML), 20166-20270, 2024
[Paper] [Code]

Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji
On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods
International Conference on Learning Representations (ICLR), 2024 (Spotlight, 5% acceptance rate)
[Paper]

Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Complete and Efficient Graph Transformers for Crystal Material Property Prediction
International Conference on Learning Representations (ICLR), 2024
[Paper] [Code]

Shurui Gui, Xiner Li, Shuiwang Ji
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
International Conference on Learning Representations (ICLR), 2024
[Paper]

Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
International Conference on Learning Representations (ICLR), 2024
[Paper] [Code]

Yaochen Xie, Yuchao Lin, Ziqian Xie, Saiful Islam, Degui Zhi, Shuiwang Ji
Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies
Transactions on Machine Learning Research, 2024
[Paper]

Meng Liu, Haiyang Yu, Shuiwang Ji
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm
Transactions on Machine Learning Research, 2024
[Paper]

Zhao Xu, Haiyang Yu, Montgomery Bohde, Shuiwang Ji
Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction
Transactions on Machine Learning Research, 2024
[Paper] [Code]

Kamal Choudhary, … , Keqiang Yan, Yuchao Lin, Shuiwang Ji, … (37 authors)
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods
npj Computational Materials, 10: 93, 2024
[Paper] [Project]

Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji
FlowX: Towards Explainable Graph Neural Networks via Message Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(7): 4567-4578, 2024
[Paper] [Code]

Youzhi Luo, Chengkai Liu, Shuiwang Ji
Towards Symmetry-Aware Generation of Periodic Materials
The 37th Conference on Neural Information Processing Systems (NeurIPS), 53308-53329, 2023
[Paper] [Code]

Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
The 37th Conference on Neural Information Processing Systems (NeurIPS), 3945-3978, 2023
[Paper] [Code]

Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P Gomes, Zhi-Ming Ma
A New Perspective on Building Efficient and Expressive 3D Equivariant Graph Neural Networks
The 37th Conference on Neural Information Processing Systems (NeurIPS), 66647–66674, 2023
[Paper] [Code]

Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
The 37th Conference on Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 40487-40503, 2023
[Paper] [Code]

Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong
Video Timeline Modeling for News Story Understanding
The 37th Conference on Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 28294-28310, 2023
[Paper] [Code]

Jacob Helwig, Xuan Zhang, Cong Fu, Jerry Kurtin, Stephan Wojtowytsch, Shuiwang Ji
Group Equivariant Fourier Neural Operators for Partial Differential Equations
International Conference on Machine Learning (ICML), 12907-12930, 2023
[Paper] [Code]

Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
International Conference on Machine Learning (ICML), 21260-21287, 2023
[Paper] [Code]

Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou
Graph Mixup with Soft Alignments
International Conference on Machine Learning (ICML), 21335-21349, 2023
[Paper] [Code]

Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian
International Conference on Machine Learning (ICML), 40412-40424, 2023
[Paper] [Code]

Meng Liu, Haoran Liu, Shuiwang Ji
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models
International Conference on Learning Representations (ICLR), 2023
[Paper] [Code]

Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji
Learning Hierarchical Protein Representations via Complete 3D Graph Networks
International Conference on Learning Representations (ICLR), 2023
[Paper] [Code]

Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou
Learning Fair Graph Representations via Automated Data Augmentations
International Conference on Learning Representations (ICLR), 2023 (Spotlight, 8% acceptance rate)
[Paper] [Code]

Youzhi Luo, Michael McThrow, Wing Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, and Shuiwang Ji
Automated Data Augmentations for Graph Classification
International Conference on Learning Representations (ICLR), 2023
[Paper] [Code]

Cong Fu, Keqiang Yan, Limei Wang, Wing Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji
A Latent Diffusion Model for Protein Structure Generation
Learning on Graphs Conference (LOG), 2023
[Paper] [Code]

Cong Fu, Jacob Helwig, Shuiwang Ji
Semi-Supervised Learning for High-Fidelity Fluid Flow Reconstruction
Learning on Graphs Conference (LOG), 2023
[Paper] [Code]

Sheng Gong, Keqiang Yan, Tian Xie, Yang Shao-Horn, Rafael Gomez-Bombarelli, Shuiwang Ji, Jeffrey Grossman
Examining graph neural networks for crystal structures: limitations and opportunities for capturing periodicity
Science Advances, 9(45)
[Paper]

Linus Manubens-Gil, … , Shuiwang Ji, … , Hanchuan Peng (65 authors)
BigNeuron: A resource to benchmark and predict best-performing algorithms for automated reconstruction of neuronal morphology
Nature Methods, 20: 824-835, 2023
[Paper]

Zhengyang Wang and Shuiwang Ji
Second-Order Pooling for Graph Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(6): 6870-6880, 2023
[Paper] [Code]

Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji
Explainability in Graph Neural Networks: A Taxonomic Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5): 5782-5799, 2023
[Paper] [Code]

Xinyi Xu, Cheng Deng, Yaochen Xie, and Shuiwang Ji
Group Contrastive Self-Supervised Learning on Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3): 3169-3180, 2023
[Paper]

Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhengyang Wang, and Shuiwang Ji
Self-Supervised Learning of Graph Neural Networks: A Unified Review
IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2): 2412-2429, 2023
[Paper] [Code]

Xinyi Xu, Zhengyang Wang, Cheng Deng, Hao Yuan, Shuiwang Ji
Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping
IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1): 1189-1200, 2023
[Paper]

Lei Cai, Zhengyang Wang, Rob Kulathinal, Sudhir Kumar, and Shuiwang Ji
Deep Low-Shot Learning for Biological Image Classification and Visualization from Limited Training Samples
IEEE Transactions on Neural Networks and Learning Systems, 34(5): 2528-2538, 2023
[Paper] [Code]

Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji
GOOD: A Graph Out-of-Distribution Benchmark
The 36th Conference on Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2059-2073, 2022
[Paper] [Code]

Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs
The 36th Conference on Neural Information Processing Systems (NeurIPS), 650-664, 2022
[Paper] [Code]

Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji
Periodic Graph Transformers for Crystal Material Property Prediction
The 36th Conference on Neural Information Processing Systems (NeurIPS), 15066-15080, 2022
[Paper] [Code]

Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji
Task-Agnostic Graph Explanations
The 36th Conference on Neural Information Processing Systems (NeurIPS), 12027-12039, 2022
[Paper] [Code]

Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji
Generating 3D Molecules for Target Protein Binding
International Conference on Machine Learning (ICML), 13912-13924, 2022 (Long presentation, 2.1% acceptance rate)
[Paper] [Code]

Yaochen Xie, Zhao Xu, Shuiwang Ji
Self-Supervised Representation Learning via Latent Graph Prediction
International Conference on Machine Learning (ICML), 24460-24477, 2022
[Paper] [Code]

Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji
GraphFM: Improving Large-Scale GNN Training via Feature Momentum
International Conference on Machine Learning (ICML), 25684-25701, 2022
[Paper] [Code]

Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, and Shuiwang Ji
Spherical Message Passing for 3D Molecular Graphs
International Conference on Learning Representations (ICLR), 2022
[Paper] [Code]

Youzhi Luo and Shuiwang Ji
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch
International Conference on Learning Representations (ICLR), 2022
[Paper] [Code]

Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2242-2252, 2022

Meng Liu and Shuiwang Ji
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences
SIAM International Conference on Data Mining (SDM), 55-63, 2022
[Paper] [Code]

Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Qi Qi, Zhuoning Yuan, Tianbao Yang, Shuiwang Ji
Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery
Bioinformatics, 38(9): 2579-2586, 2022
[Paper] [Code] [AI Cures #1]

Meng Liu, Zhengyang Wang, and Shuiwang Ji
Non-Local Graph Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(12): 10270-10276, 2022
[Paper] [Code]

Lei Cai, Jundong Li, Jie Wang, and Shuiwang Ji
Line Graph Neural Networks for Link Prediction
IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(9): 5103-5113, 2022
[Paper] [Code]

Hao Yuan, Lei Cai, Xia Hu, Jie Wang, and Shuiwang Ji
Interpreting Image Classifiers by Generating Discrete Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(4): 2019-2030, 2022
[Paper]

Yaochen Xie, Yu Ding, Shuiwang Ji
Augmented Equivariant Attention Networks for Microscopy Image Transformation
IEEE Transactions on Medical Imaging, 41(11): 3194-3206, 2022
[Paper] [Code]

Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, and Shuiwang Ji
DIG: A Turnkey Library for Diving into Graph Deep Learning Research
Journal of Machine Learning Research, 22(240):1-9, 2021
[Paper] [Code]

Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, and Tianbao Yang
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence
The 35th Annual Conference on Neural Information Processing Systems (NeurIPS), 1752-1765, 2021
[Paper] [Code]

Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, and Feng Wu
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
The 35th Annual Conference on Neural Information Processing Systems (NeurIPS), 19172-19183, 2021

Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, and Shuiwang Ji
On Explainability of Graph Neural Networks via Subgraph Explorations
The 38th International Conference on Machine Learning (ICML), 12241-12252, 2021
[Paper] [Code]

Youzhi Luo, Keqiang Yan, Shuiwang Ji
GraphDF: A Discrete Flow Model for Molecular Graph Generation
The 38th International Conference on Machine Learning (ICML), 7192-7203, 2021
[Paper] [Code]

Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, and Jundong Li
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter
ACM International Conference on Information and Knowledge Management (CIKM), 392-401, 2021

Meng Liu, Keqiang Yan, Bora Oztekin, and Shuiwang Ji
GraphEBM: Molecular Graph Generation with Energy-Based Models
International Conference on Learning Representations Workshop on Energy Based Models, 2021
[Paper] [Code]

Zhengyang Wang, Yaochen Xie, and Shuiwang Ji
Global Voxel Transformer Networks for Augmented Microscopy
Nature Machine Intelligence, 3: 161-171, 2021
[Paper] [Code] [Video] [TAMU News]

Hongyang Gao, Yi Liu, and Shuiwang Ji
Topology-Aware Graph Pooling Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(12): 4512-4518, 2021

Hongyang Gao, Zhengyang Wang, Lei Cai, and Shuiwang Ji
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions
IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(8): 2570-2581, 2021
[Paper] [Code]

Yi Liu and Shuiwang Ji
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection from Brain Electron Microscopy
IEEE Transactions on Medical Imaging, 40(12): 3507-3518, 2021
[Paper] [#1 on MICCAI Challenge on CREMI Leaderboard]

Zhengyang Wang and Shuiwang Ji
Smoothed Dilated Convolutions for Improved Dense Prediction
Data Mining and Knowledge Discovery, 35(4): 1470-1496, 2021
[Paper] [Code]

Yingying Wang, Lei Cai, Wei Chen, Difei Wang, Shi Xu, Limei Wang, Martin A. Kononov, Shuiwang Ji, and Ming Xian
Development of xanthene-based fluorescent dyes: machine learning-assisted prediction vs TD-DFT prediction and experimental validation
Chemistry-Methods, 1(8): 389-396, 2021
[Paper] [Code]

Yaochen Xie, Zhengyang Wang, and Shuiwang Ji
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising
The 34th Annual Conference on Neural Information Processing Systems (NeurIPS), 20320-20330, 2020
[Paper] [Code] [Demo]

Hao Yuan and Shuiwang Ji
StructPool: Structured Graph Pooling via Conditional Random Fields
The 8th International Conference on Learning Representations (ICLR), 2020
[Paper] [Code]

Hongyang Gao, Zhengyang Wang, and Shuiwang Ji
Kronecker Attention Networks
The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 229-237, 2020

Meng Liu, Hongyang Gao, and Shuiwang Ji
Towards Deeper Graph Neural Networks
The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 338-348, 2020
[Paper] [Code]

Hao Yuan, Jiliang Tang, Xia Hu, and Shuiwang Ji
XGNN: Towards Model-Level Explanations of Graph Neural Networks
The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 430-438, 2020
[Paper] [Code]

Yi Liu, Hao Yuan, Lei Cai, and Shuiwang Ji
Deep Learning of High-Order Interactions for Protein Interface Prediction
The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 679-687, 2020

Hongyang Gao, Lei Cai, and Shuiwang Ji
Adaptive Convolutional ReLUs
The 34th AAAI Conference on Artificial Intelligence (AAAI), 3914-3921, 2020

Zhengyang Wang, Na Zou, Dinggang Shen, and Shuiwang Ji
Non-local U-Nets for Biomedical Image Segmentation
The 34th AAAI Conference on Artificial Intelligence (AAAI), 6315-6322, 2020
[Paper] [Code]

Lei Cai and Shuiwang Ji
A Multi-Scale Approach for Graph Link Prediction
The 34th AAAI Conference on Artificial Intelligence (AAAI), 3308-3315, 2020

Hanzi Mao, Xi Liu, Nick Duffield, Hao Yuan, Shuiwang Ji, and Binayak Mohanty
Context-Aware Deep Representation Learning for Geo-Spatiotemporal Analysis
IEEE International Conference on Data Mining (ICDM), 392-401, 2020

Zhengyang Wang, Bunyamin Sisman, Hao Wei, Xin Luna Dong, and Shuiwang Ji
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage
IEEE International Conference on Data Mining (ICDM), 1322-1327, 2020

Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu
Deep Neural Networks with Knowledge Instillation
SIAM International Conference on Data Mining (SDM), 370-378, 2020

Hongyang Gao, Hao Yuan, Zhengyang Wang, and Shuiwang Ji
Pixel Transposed Convolutional Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(5): 1218-1227, 2020
[Paper] [Code]

Yi Liu, Hao Yuan, Zhengyang Wang, and Shuiwang Ji
Global Pixel Transformers for Virtual Staining of Microscopy Images
IEEE Transactions on Medical Imaging, 39(6): 2256-2266, 2020
[Paper] [Code]

Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, and Shuiwang Ji
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis
IEEE Transactions on Big Data, 6(2): 322-333, 2020

Hao Yuan, Lei Cai, Zhengyang Wang, Xia Hu, Shaoting Zhang, and Shuiwang Ji
Computational Modeling of Cellular Structures Using Conditional Deep Generative Networks
Bioinformatics, 35(12): 2141-2149, 2019
[Paper] [Code]

Debrup Banerjee, Kazi Islam, Keyi Xue, Gang Mei, Lemin Xiao, Guangfan Zhang, Roger Xu, Lei Cai, Shuiwang Ji, and Jiang Li
A Deep Transfer Learning Approach for Improved Post Traumatic Stress Disorder Diagnosis
Knowledge and Information Systems, 60(3): 1693-1724, 2019

Hongyang Gao and Shuiwang Ji
Graph U-Nets
The 36th International Conference on Machine Learning (ICML), 2083-2092, 2019
[Code]

Hongyang Gao and Shuiwang Ji
Graph Representation Learning via Hard and Channel-Wise Attention Networks
The 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 741-749, 2019

Lei Cai and Shuiwang Ji
An Efficient Policy Gradient Method for Conditional Dialogue Generation
The 19th IEEE International Conference on Data Mining (ICDM), 31-40, 2019

Hao Yuan, Na Zou, Shaoting Zhang, Hanchuan Peng, and Shuiwang Ji
Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction
The 19th IEEE International Conference on Data Mining (ICDM), 806-815, 2019
[Paper] [Code]

Yi Liu, Hao Yuan, and Shuiwang Ji
Leaning Local and Global Multi-Context Representations for Document Classification
The 19th IEEE International Conference on Data Mining (ICDM), 1234-1239, 2019

Hongyang Gao, Yongjun Chen, and Shuiwang Ji
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations
The Web Conference (WWW), 2743-2749, 2019

Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, and Xia Hu
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition
The Web Conference (WWW), 383-393, 2019

Fan Yang, Shiva Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric Ragan, Shuiwang Ji, and Xia Hu
XFake: Explainable Fake News Detector with Visualizations
The Web Conference (WWW), Demonstrations Track, 3600-3604, 2019

Hao Yuan, Yongjun Chen, Xia Hu, and Shuiwang Ji
Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods
The 33rd AAAI Conference on Artificial Intelligence (AAAI), 5717-5724, 2019

Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, and Shuiwang Ji
Dense Transformer Networks for Brain Electron Microscopy Image Segmentation
The 28th International Joint Conference on Artificial Intelligence (IJCAI), 2894-2900, 2019

Zhengyang Wang, Hao Yuan, and Shuiwang Ji
Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions
The SIAM International Conference on Data Mining (SDM), 648-656, 2019

Lei Cai, Hongyang Gao, and Shuiwang Ji
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation
The SIAM International Conference on Data Mining (SDM), 630-638, 2019

Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu
An Interpretable Neural Model with Interactive Stepwise Influence
The 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 528-540, 2019

Hongyang Gao, Zhengyang Wang, and Shuiwang Ji
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions
The 32nd Annual Conference on Neural Information Processing Systems (NeurIPS), 5203-5211, 2018
[paper] [code]

Zhengyang Wang and Shuiwang Ji
Smoothed Dilated Convolutions for Improved Dense Prediction
The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2486-2495, 2018

Yongjun Chen, Hongyang Gao, Lei Cai, Min Shi, Dinggang Shen, and Shuiwang Ji
Voxel Deconvolutional Networks for 3D Brain Image Labeling
The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1226-1234, 2018

Hongyang Gao, Zhengyang Wang, and Shuiwang Ji
Large-Scale Learnable Graph Convolutional Networks
The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1416-1424, 2018
[Code]

Lei Cai, Zhengyang Wang, Hongyang Gao, Dinggang Shen, and Shuiwang Ji
Deep Adversarial Learning for Multi-Modality Missing Data Completion
The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1158-1166, 2018
[Code]

Zhengyang Wang and Shuiwang Ji
Learning Convolutional Text Representations for Visual Question Answering
The SIAM International Conference on Data Mining (SDM), 594-602, 2018
[code]

Lei Cai, Bian Wu, and Shuiwang Ji
Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli
Neuroinformatics, 16(3):473-488, 2018

Zhongyu Li, Erik Butler, Kang Li, Aidong Lu, Shuiwang Ji, and Shaoting Zhang
Large-Scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality
Neuroinformatics, 16(3):339-349, 2018

Lei Zhang, Yao Zhao, Zhenfeng Zhu, Dinggang Shen, and Shuiwang Ji
Multi-View Missing Data Completion
IEEE Transactions on Knowledge and Data Engineering, 30(7): 1296-1309, 2018

Tao Zeng, Bian Wu, Jiayu Zhou, Ian Davidson and Shuiwang Ji
Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction
The IEEE International Conference on Data Mining (ICDM), 1165-1170, 2017

Hongyang Gao and Shuiwang Ji
Efficient and Invariant Convolutional Neural Networks for Dense Prediction
The IEEE International Conference on Data Mining (ICDM), 871-876, 2017

Debrup Banerjee, Kazi Islam, Gang Mei, Lemin Xiao, Roger Xu, Shuiwang Ji, and Jiang Li
A Deep Transfer Learning Approach for Post Traumatic Stress Disorder Diagnosis
The IEEE International Conference on Data Mining (ICDM), 11-20, 2017

Qi Wang, Mengying Sun, Liang Zhan, Paul Thompson, Shuiwang Ji, and Jiayu Zhou
Multi-Modality Disease Modeling via Collective Deep Matrix Factorization
The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1155-1164, 2017

Tao Zeng, Bian Wu, and Shuiwang Ji
DeepEM3D: Approaching human-level performance on 3D anisotropic EM image segmentation
Bioinformatics, 33(16): 2555-2562, 2017 (Impact factor: 7.307)

Rongjian Li, Tao Zeng, Hanchuan Peng, and Shuiwang Ji
Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction
IEEE Transactions on Medical Imaging, 36(7):1533-1541, 2017

Ahmed Fakhry, Tao Zeng, and Shuiwang Ji
Residual Deconvolutional Networks for Brain Electron Microscopy Image Segmentation
IEEE Transactions on Medical Imaging, 36(2):447-456, 2017

Jie Gui, Zhenan Sun, Shuiwang Ji, Dacheng Tao, and Tieniu Tan
Feature Selection Based on Structured Sparsity: A Comprehensive Study
IEEE Transactions on Neural Networks and Learning Systems, 28(7):1490-1507, 2017

Ahmed Fakhry, Hanchuan Peng, and Shuiwang Ji
Deep models for brain EM image segmentation: novel insights and improved performance
Bioinformatics, 32: 2352-2358, 2016 (5-Yr impact factor: 7.685)

Rongjian Li, Dong Si, Tao Zeng, Shuiwang Ji, and Jing He
Deep Convolutional Neural Networks for Detecting Secondary Structures in Protein Density Maps from Cryo-Electron Microscopy
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 41-46, 2016

Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul Thompson, Jieping Ye, and Jie Wang
Parallel Lasso Screening for Big Data Optimization
The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1705-1714, 2016

Kaixiang Lin, Jianpeng Xu, Inci Baytas, Shuiwang Ji, and Jiayu Zhou
Multi-Task Feature Interaction Learning
The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1735-1744, 2016

Lei Zhang, Shupeng Wang, Xiaoyu Zhang, Yong Wang, Binbin Li, Dinggang Shen, and Shuiwang Ji
Collaborative Multi-View Denoising
The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2045-2054, 2016

Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, and Jiang Li
A Robust Deep Model for Improved Classification of AD/MCI Patients
IEEE Journal of Biomedical and Health Informatics, 19(5):1610-1616, 2015

Tao Zeng, Hanbo Chen, Ahmed Fakhry, Xiaoping Hu, Tianming Liu, and Shuiwang Ji
Allen Mouse Brain Atlases Reveal Different Neural Connection and Gene Expression Patterns in Cerebellum Gyri and Sulci
Brain Structure and Function, 220(5):2691-2703, 2015

Tao Zeng and Shuiwang Ji
Deep Convolutional Neural Networks for Multi-Instance Multi-Task Learning
The IEEE International Conference on Data Mining (ICDM), 579-588, 2015

Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, and Shuiwang Ji
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis
The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1475-1484, 2015

Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye
Structural Graphical Lasso for Learning Mouse Brain Connectivity
The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 1385-1394, 2015

Wenlu Zhang, Rongjian Li, Houtao Deng, Li Wang, Weili Lin, Shuiwang Ji, and Dinggang Shen
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
NeuroImage, 108:214-224, 2015

Wenlu Zhang, Rongjian Li, Daming Feng, Andrey Chernikov, Nikos Chrisochoides, Christopher Osgood, and Shuiwang Ji
Evolutionary Soft Co-Clustering: Formulations, Algorithms, and Applications
Data Mining and Knowledge Discovery, 29(3):765-791, 2015

Rongjian Li, Wenlu Zhang, Yao Zhao, Zhenfeng Zhu, and Shuiwang Ji
Sparsity Learning Formulations for Mining Time-Varying Data
IEEE Transactions on Knowledge and Data Engineering, 27(5): 1411-1423, 2015

Tao Zeng, Rongjian Li, Ravi Mukkamala, Jieping Ye, and Shuiwang Ji
Deep convolutional neural networks for annotating gene expression patterns in the mouse brain
BMC Bioinformatics, 16:147, 2015

Ahmed Fakhry, Tao Zeng, Hanchuan Peng, and Shuiwang Ji
Global Analysis of Gene Expression and Projection Target Correlations in the Mouse Brain
Brain Informatics, 2(2): 107-117, 2015

Ahmed Fakhry and Shuiwang Ji
High-Resolution Prediction of Mouse Brain Connectivity Using Gene Expression Patterns
Methods, 73:71-78, 2015

Tao Yang, Xinlin Zhao, Binbin Lin, Tao Zeng, Shuiwang Ji, and Jieping Ye
Automated Gene Expression Pattern Annotation in the Mouse Brain
The 20th Pacific Symposium on Biocomputing (PSB), 144-155, 2015

Rongjian Li, Wenlu Zhang, Heung-Il Suk, Li Wang, Jiang Li, Dinggang Shen, and Shuiwang Ji
Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis
The Seventeenth International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 305-312, 2014

Feng Li, Loc Tran, Kim-Ham Thung, Shuiwang Ji, Dinggang Shen, and Jiang Li
Robust Deep Learning for Improved Classification of AD/MCI Patients
The Fifth MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), 2014

Rongjian Li, Wenlu Zhang, and Shuiwang Ji
Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns
BMC Bioinformatics, 15:209, 2014

Shuiwang Ji, Ahmed Fakhry, and Houtao Deng
Integrative analysis of the connectivity and gene expression atlases in the mouse brain
NeuroImage, 84(1):245-253, 2014 (Impact Factor: 6.252)

Lei Yuan, Cheng Pan, Shuiwang Ji, Michael McCutchan, Zhi-Hua Zhou, Stuart Newfeld, Sudhir Kumar, and Jieping Ye
Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression
Bioinformatics, 30(2):266-273, 2014 [Project page] (5-Yr Impact Factor: 6.911)

Jie Gui, Zhenan Sun, Jun Cheng, Shuiwang Ji, and Xindong Wu
How to Estimate the Regularization Parameter for Spectral Regression Discriminant Analysis and Its Kernel Version?
IEEE Transactions on Circuits and Systems for Video Technology, 24(2):211-223, 2014

Liang Sun, Shuiwang Ji, and Jieping Ye
Multi-Label Dimensionality Reduction
Chapman and Hall/CRC, 2014

Wenlu Zhang, Daming Feng, Rongjian Li, Andrey Chernikov, Nikos Chrisochoides, Christopher Osgood, Charlotte Konikoff, Stuart Newfeld, Sudhir Kumar, and Shuiwang Ji
A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis
BMC Bioinformatics, 14:372, 2013 [Software]

Qian Sun, Sherin Muckatira, Lei Yuan, Shuiwang Ji, Stuart Newfeld, Sudhir Kumar, and Jieping Ye
Image-level and group-level models for Drosophila gene expression pattern annotation
BMC Bioinformatics, 14:350, 2013

Shuiwang Ji
Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering
BMC Bioinformatics, 14:222, 2013

Shuiwang Ji, Wenlu Zhang, and Rongjian Li
A Probabilistic Latent Semantic Analysis Model for CoClustering the Mouse Brain Atlas
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(6):1460-1468, 2013

Shuiwang Ji, Wei Xu, Ming Yang, and Kai Yu
3D Convolutional Neural Networks for Human Action Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(1):221-231, 2013

Xinhai Liu, Shuiwang Ji, Wolfgang Glanzel, and Bart De Moor
Multiview Partitioning via Tensor Methods
IEEE Transactions on Knowledge and Data Engineering, 25(5):1056-1069, 2013

Wenlu Zhang, Shuiwang Ji, and Rui Zhang
Evolutionary Soft Co-Clustering
The 2013 SIAM International Conference on Data Mining (SDM 2013), 121-129, 2013

Shuiwang Ji, Wenlu Zhang, and Jun Liu
A Sparsity-Inducing Formulation for Evolutionary Co-Clustering
The Eighteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2012), 334-342, 2012

Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, and Michele C. Weigle
Demographic Prediction of Mobile User from Phone Usage
Mobile Data Challenge Workshop, Nokia Research Center, 2012
Second Prize on Demographic Prediction

Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, and Jieping Ye
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
BMC Bioinformatics 2012, 13:107

Dong Si, Shuiwang Ji, Kamal Al Nasr, and Jing He
A Machine Learning Approach for the Identification of Protein Secondary Structure Elements from Electron Cryo-Microscopy Density Maps
Biopolymers, 97(9):698-708, 2012

Jie Gui, Zhenan Sun, Wei Jia, Rongxiang Hu, Yingke Lei, and Shuiwang Ji
Discriminant Sparse Neighborhood Preserving Embedding for Face Recognition
Pattern Recognition, 45(8):2884-2893, 2012
Top 25 Hottest Articles

Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye and Zhi-Hua Zhou
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(1):98-112, 2012

Shuiwang Ji
Computational network analysis of the anatomical and genetic organizations in the mouse brain
Bioinformatics, 27(23):3293-3299, 2011

Sudhir Kumar, Charlotte Konikoff, Bernard Van Emden, Christopher Busick, Kailah T. Davis, Shuiwang Ji, Lin-Wei Wu, Hector Ramos, Thomas Brody, Sethuraman Panchanathan, Jieping Ye, Timothy L. Karr, Kristyn Gerold, Michael McCutchan and Stuart J. Newfeld
FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis
Bioinformatics, 27(23):3319-3320, 2011

Liang Sun, Shuiwang Ji and Jieping Ye
Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(1):194-200, 2011

Ting Kei Pong, Paul Tseng, Shuiwang Ji and Jieping Ye
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
SIAM Journal on Optimization, 20(6):3465-3489, 2010

Shuiwang Ji, Wei Xu, Ming Yang and Kai Yu
3D Convolutional Neural Networks for Human Action Recognition
The Twenty-Seventh International Conference on Machine Learning (ICML 2010), 495-502, 2010

Shuiwang Ji
Computational Analysis of Drosophila Gene Expression Pattern Images
PhD Dissertation, Arizona State University, 2010.
Dissertation Committee: Jieping Ye (Chair), Subbarao Kambhampati, Sudhir Kumar, and Huan Liu

Shuiwang Ji, Lei Tang, Shipeng Yu and Jieping Ye
A Shared-Subspace Learning Framework for Multi-Label Classification
ACM Transactions on Knowledge Discovery from Data, 4(2):1-29, 2010

Shuiwang Ji, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar and Jieping Ye
A Bag-of-Words Approach for Drosophila Gene Expression Pattern Annotation
BMC Bioinformatics, 10(1):119, 2009

Jun Liu, Shuiwang Ji and Jieping Ye
Multi-Task Feature Learning via Efficient L21-Norm Minimization
The Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI 2009), 339-348, 2009

Shuiwang Ji and Jieping Ye
An Accelerated Gradient Method for Trace Norm Minimization
The Twenty-Sixth International Conference on Machine Learning (ICML 2009), 457-464, 2009

Liang Sun, Shuiwang Ji and Jieping Ye
A Least Squares Formulation for a Class of Generalized Eigenvalue Problems in Machine Learning
The Twenty-Sixth International Conference on Machine Learning (ICML 2009), 977-984, 2009

Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar and Jieping Ye
Drosophila Gene Expression Pattern Annotation Using Sparse Features and Term-term Interactions
The Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2009), 407-416, 2009

Bao-Hong Shen, Shuiwang Ji and Jieping Ye
Mining Discrete Patterns via Binary Matrix Factorization
The Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2009), 757-766, 2009

Shuiwang Ji and Jieping Ye
Linear Dimensionality Reduction for Multi-Label Classification
The Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009), 1077-1082, 2009

Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye and Zhi-Hua Zhou
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning
The Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009), 1445-1450, 2009

Liang Sun, Shuiwang Ji and Jieping Ye
On the Equivalence Between Canonical Correlation Analysis and Orthonormalized Partial Least Squares
The Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009), 1230-1235, 2009

Ming Yang, Shuiwang Ji, Wei Xu, Jinjun Wang, Fengjun Lv, Kai Yu, Yihong Gong, Mert Dikmen, Dennis J. Lin and Thomas S. Huang
Detecting Human Actions in Surveillance Videos
TREC Video Retrieval Evaluation Workshop, 2009

Jieping Ye and Shuiwang Ji
Discriminant Analysis for Dimensionality Reduction: An Overview of Recent Developments
in N. Boulgouris and K. N. Plataniotis and E. Micheli-Tzanakou (Eds), Biometrics: Theory, Methods, and Applications, 1-19, Wiley-IEEE Press, New York, 2009

Jun Liu, Shuiwang Ji and Jieping Ye
SLEP: Sparse Learning with Efficient Projections
Arizona State University, 2009

Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar and Jieping Ye
Automated Annotation of Drosophila Gene Expression Patterns Using a Controlled Vocabulary
Bioinformatics, 24(17):1881-1888, 2008

Liang Sun, Shuiwang Ji and Jieping Ye
Adaptive Diffusion Kernel Learning from Biological Networks for Protein Function Prediction
BMC Bioinformatics, 9:162, 2008

Jieping Ye, Shuiwang Ji and Jianhui Chen
Multi-class Discriminant Kernel Learning via Convex Programming
Journal of Machine Learning Research, 9:719-758, 2008

Shuiwang Ji and Jieping Ye
Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study
IEEE Transactions on Knowledge and Data Engineering, 20(10):1311-1321, 2008

Shuiwang Ji and Jieping Ye
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection
IEEE Transactions on Neural Networks, 19(10):1768-1782, 2008

Shuiwang Ji, Liang Sun, Rong Jin and Jieping Ye
Multi-Label Multiple Kernel Learning
The Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), 777-784, 2008

Shuiwang Ji, Lei Tang, Shipeng Yu and Jieping Ye
Extracting Shared Subspace for Multi-Label Classification
The Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), 381-389, 2008

Liang Sun, Shuiwang Ji and Jieping Ye
Hypergraph Spectral Learning for Multi-Label Classification
The Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), 668-676, 2008

Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu and Jieping Ye
Learning Subspace Kernels for Classification
The Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), 106-114, 2008

Liang Sun, Shuiwang Ji and Jieping Ye
A Least Squares Formulation for Canonical Correlation Analysis
The Twenty-Fifth International Conference on Machine Learning (ICML 2008), 1024-1031, 2008

Shuiwang Ji and Jieping Ye
A Unified Framework for Generalized Linear Discriminant Analysis
The IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 1-7, 2008

Jieping Ye, Shuiwang Ji and Jianhui Chen
Learning the Kernel Matrix in Discriminant Analysis via Quadratically Constrained Quadratic Programming
The Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2007), 854-863, 2007

Jieping Ye, Jianhui Chen and Shuiwang Ji
Discriminant Kernel and Regularization Parameter Learning via Semidefinite Programming
The Twenty-Fourth International Conference on Machine Learning (ICML 2007), 1095-1102, 2007