Search, Search, and Research. On this exploration Odyssey, silence is golden. Learning comes from errors.

Research interests

My most recent interests are focusing on mathematics for data sciences, in particular topological and geometric methods for high dimensional data analysis and statistical machine learning, with applications in computational biology and information technology.

Monograph

A Dynamic Theory of Learning. PhD Dissertation, University of Calfornia at Berkeley. Supervisor: Steve Smale. December, 2006.
Published as A Dynamic Theory of Learning -- Online Learning and Stochastic Algorithms in Reproducing Kernel Hilbert Spaces, Verlag Dr. Muller, ISBN: 978-3-639-09390-2. 2008.

A Mathematical Introduction to Data Analysis. preprint.

Papers and Preprints

• UniGAD: Unifying Multi-level Graph Anomaly Detection.
  Yiqing Lin, Jianheng Tang, Chenyi Zi, H. Vicky Zhao, Yuan Yao, Jia Li.
  The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, December 10-15, 2024.

• Towards Global Optimal Visual In-Context Learning Prompt Selection.
  Chengming Xu, Chen Liu, Yikai Wang, Yuan Yao, Yanwei Fu.
  The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, December 10-15, 2024.

• A Biosafety-aware Framework for Generative Enzyme Design with Foundation Models.
  Xiaoyi Fu, Tao Han, Yuan Yao, Song Guo.
  The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Workshop on Foundation Models for Science: Progress, Opportunities, and Challenges (FM4Science), Vancouver, Canada, December 10-15, 2024.

• Mitigating the Alignment Tax of RLHF.
  Yong Lin, Hangyu Lin, Wei Xiong, Shizhe Diao, Jianmeng Liu, Jipeng Zhang, Rui Pan, Haoxiang Wang, Wenbin Hu, Hanning Zhang, Hanze Dong, Renjie Pi, Han Zhao, Nan Jiang, Heng Ji, Yuan Yao, Tong Zhang.
  The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, Florida, November 12-16, 2024.
  [ arXiv:2309.06256 ]

• PRESTO: Progressive Pretraining Enhances Synthetic Chemistry Outcomes.
  He Cao, Yanjun Shao, Zhiyuan Liu, Zijing Liu, Xiangru Tang, Yuan Yao, Yu Li.
  The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, Florida, November 12-16, 2024.
  [ arXiv:2406.13193 ]

• MoleculeQA: A Dataset to Evaluate Factual Accuracy in Molecular Comprehension.
  Xingyu Lu, He Cao, Zijing Liu, Shengyuan Bai, Leqing Chen, Yuan Yao, Hai-Tao Zheng, Yu Li.
  The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, Florida, November 12-16, 2024.
  [ arXiv:2403.08192 ]

• PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models.
  Haoran Li, Dadi Guo, Donghao Li, Wei Fan, Qi Hu, Xin Liu, Chunkit Chan, Duanyi Yao, Yuan Yao, Yangqiu Song
  The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand, August 11-16, 2024.
  [ arXiv:2311.04044 ]

• Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion.
  Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao.
  The 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024.
  [ arXiv:2402.16305 ]

• Learning Long Timescale in Molecular Dynamics by Nano-GPT.
  Wenqi Zeng, Yuan Yao.
  The 41st International Conference on Machine Learning (ICML 2024), AI for Science Workshop, Vienna, Austria, PMLR 235, July 21-27, 2024.
  [ link ]

• FedAdOb: Privacy-Preserving Federated Deep Learning with Adaptive Obfuscation.
  Hanlin Gu, Jiahuan Luo, Yan Kang, Yuan Yao, Gongxi Zhu, Bowen Li, Lixin Fan, Qiang Yang.
  [ arXiv:2406.01085 ]

• A Generalization Theory of Cross-Modality Distillation with Contrastive Learning.
  Hangyu Lin, Chen Liu, Chengming Xu, Zhengqi Gao, Yanwei Fu, Yuan Yao.
  The Twelfth International Conference on Learning Representations (ICLR 2024), Workshop on Bridging the Gap Between Practice and Theory in Deep Learning (BGPT), Vienna, Austria, May 7-11, 2024.
  [ arXiv:2405.03355 ]

• Unveiling the hidden reaction kinetic network of carbon in water with first-principles Markov state models.
  Chu Li, Yuan Yao, Ding Pan
  Proceedings of the National Academy of Sciences of the United States of America (PNAS), preprint, 2024.
  [ arXiv:2401.07019 ]

• Investigation of the Flipping Dynamics of 1, N6-Ethenoadenine in Alkyladenine DNA Glycosylase.
  Bin Liu, Yanping Qi, Xiaowei Wang, Xin Gao, Yuan Yao, and Lu Zhang.
  J. Phys. Chem. B, 2024, 128, 7, 1606--1617.
  [ DOI: https://doi.org/10.1021/acs.jpcb.3c06853 ]

• Split Knockoffs for Multiple Comparisons: Controlling the Directional False Discovery Rate.
  Yang Cao, Xinwei Sun, Yuan Yao
  Journal of the American Statistical Association, 2023. DOI: 10.1080/01621459.2023.2279292
  [ arXiv:2310.07605 ][ https://doi.org/10.1080/01621459.2023.2279292 ]

• Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning.
  Yong Lin, Chen Liu, Chenlu Ye, Qing Lian, Yuan Yao, Tong Zhang
  [ arXiv:2309.02476 ]

• Random Smoothing Regularization in Kernel Gradient Descent Learning.
  Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan Yao
  Journal of Machine Learning Research, 25(284): 1-88, 2024.
  [ arXiv:2305.03531 ]

• Inducing Neural Collapse in Deep Long-tailed Learning.
  Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Lujia Pan, Yuan Yao
  Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, PMLR: Volume 206. April 25-27, 2023.
  [ arXiv:2302.12453 ]

• SurfBind: Surface Distance aided Geometric Deep Learning for Binding Conformations.
  Jiamin Wu, Wenqi Zeng, Song Liu, Yuan Yao
  The 37th AAAI Conference on Artificial Intelligence: The Ninth International Workshop on Deep Learning on Graphs (DLG-AAAI'23), Washington, DC, USA. February 7-14, 2023.
  [ pdf ] [ link ]

• Exploring Vision Transformers as Diffusion Learners.
  He Cao, J Wang, T Ren, X Qi, Y Chen, Y Yao, L Zhang
  [ arXiv:2212.13771 ]

• StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding.
  Jinshan Zeng, Y Wang, Q Chen, Y Liu, M Wang, Y Yao
  [ arXiv:2211.06198 ]

• Optimal Private Streaming SCO in $\ell_p$-geometry with Applications in High Dimensional Online Decision Making.
  Yuxuan Han, Zhicong Liang, Zhipeng Liang, Yang Wang, Yuan Yao, and Jiheng Zhang
  Proceedings of the 39th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, PMLR 162, July 17-23, 2022.
  [ arXiv:2206.08111 ][ icml version ][ GitHub ]

• NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data Release.
  Donghao Li, Yang Cao, Yuan Yao
  Conference on Parsimony and Learning (CPAL), Hong Kong, PMLR 234:480-514, Jan 3-6, 2024.
  [ arXiv:2202.06467 ][ link ][ openreview ]

• SARS-CoV-2 RNA-Dependent RNA Polymerase Follows Asynchronous Translocation Pathway for Viral Transcription and Replication.
  Xiaowei Wang, Tiantian Xu, Yuan Yao, Peter Pak-Hang Cheung, Xin Gao, and Lu Zhang
  The Journal of Physical Chemistry Letters, 14(45):10119–10128, Nov. 3, 2023.
  [ DOI: 10.26434/chemrxiv-2022-7t1jg ][ https://doi.org/10.1021/acs.jpclett.3c01249 ]

• Unveiling the ``Template-dependent" Inhibition on the Viral Transcription of SARS-CoV-2.
  Luo, Xueying, Xiaowei Wang, Yuan Yao, Xin Gao, and Lu Zhang
  The Journal of Physical Chemistry Letters. 13(31): 7197-7205, July 30, 2022.
  [ DOI: 10.1021/acs.jpclett.2c01314 ]

• Exploring Structural Sparsity of Deep Networks via Inverse Scale Spaces.
  Yanwei Fu, Chen Liu, Donghao Li, Zuyuan Zhong, Xinwei Sun, Jinshan Zeng, and Yuan Yao.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(2):1749-1765, 2023.
  [ arXiv:1905.09449 ][ DOI: 10.1109/TPAMI.2022.3168881][ GitHub source ]

• RPnet: A Reverse Projection Based Neural Network for Coarse-graining Metastable Conformational States for Protein Dynamics.
  Hanlin Gu, Wei Wang, Siqin Cao, Ilona Christy Unarta, Yuan Yao, Fu Kit Sheong, Xuhui Huang
  Physical Chemistry Chemical Physics, 2022, 24, 1462-1474. DOI: 10.1039/D1CP03622J
  [ https://www.biorxiv.org/content/10.1101/2021.08.04.455071v1 ]

• Federated Deep Learning with Bayesian Privacy.
  Hanlin Gu, Lixin Fan, Bowen Li, Yan Kang, Yuan Yao, Qiang Yang
  [ arXiv:2109.13012 ]

• A Note on Learning Rare Events in Molecular Dynamics using LSTM and Transformer.
  Wenqi Zeng, Siqin Cao, Xuhui Huang, Yuan Yao
  [ arXiv:2107.06573 ][ Github ]

• An Efficient Method to Quantify Structural Distributions in Heterogeneous cryo-EM Datasets.
  Hanlin Gu, Wei Wang, Ilona Christy Unarta, Wenqi Zeng, Fu Kit Sheong, Peter Cheung, Song Liu, Yuan Yao, and Xuhui Huang
  [ bioRxiv:10.1101/2021.05.27.446075 ][ Github ]

• Controlling the False Discovery Rate in Transformational Sparsity: Split Knockoffs.
  Yang Cao, Xinwei Sun and Yuan Yao
  Journal of Royal Statistical Society: Series B (Statistical Methodology), Volume 86, Issue 2, April 2024, Pages 386-410. DOI:10.1093/jrsssb/qkad126
  [ arXiv:2103.16159 ][DOI:10.1093/jrsssb/qkad126 ][ Github for Matlab ][ R package, by Haoxue WANG ]

• Evaluating Visual Properties via Robust HodgeRank
  Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang and Yuan Yao
  International Journal of Computer Vision, 129: 1732-1753, 2021.
  [ arXiv:1408.3467 ] [ DOI: 10.1007/s11263-021-01438-y ]

• On Stochastic Variance Reduced Gradient Method for Semidefinite Optimization.
  Jinshan Zeng, Yixuan Zha, Ke Ma, Yuan Yao
  [ arXiv:2101.00236 ]

• Not All Samples are Trustworthy: Towards Deep Robust SVP Prediction.
  Xu, Qianqian; Yang, Zhiyong; Jiang, Yangbangyan; Cao, Xiaochun; Yao, Yuan; Huang, Qingming
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(6):3154-3169, June 2022.
  [DOI: 10.1109/TPAMI.2020.3047817 ][ GitHub ]

• StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding.
  Jinshan Zeng, Qi Chen, Yunxin Liu, Mingwen Wang, Yuan Yao
  AAAI Conference on Artificial Intelligence (AAAI), Feb 2-9, 2021.
  [ arXiv:2012.08687 ][ GitHub ]

• Deep Partial Rank Aggregation for Personalized Attributes.
  Qianqian Xu, Zhiyong Yang, Zuyao Chen, Yangbangyan Jiang, Xiaochun Cao, Yuan Yao and Qingming Huang.
  AAAI Conference on Artificial Intelligence (AAAI), Feb 2-9, 2021.
  [ pdf ][ GitHub ]

• Adversarial Robustness of Stabilized Neural ODEs Might be from Obfuscated Gradients.
  Yifei Huang, Yaodong Yu, Hongyang Zhang, Yi Ma, Yuan Yao
  Mathematical and Scientific Machine Learning (MSML), August 16-19, 2021.
  [ arXiv:2009.13145 ][ GitHub ]

• Generative Adversarial Networks for Robust Cryo-EM Image Denoising.
  Hanlin Gu, Ilona Christy Unarta, Xuhui Huang, Yuan Yao
  Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, by Ke Chen (Editor), Carola-Bibiane Sch\"{o}nlieb (Editor), Xue-Cheng Tai (Editor), Laurent Younes (Editor), Springer, 2022.
  [ arXiv:2008.07307 ][ https://doi.org/10.1007/978-3-030-03009-4_126-1 ]

• How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning.
  Yikai Wang, Li Zhang, Yuan Yao, Yanwei Fu
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(10):6240-6253, 01 October 2022.
  [ arXiv:2007.08461 ][DOI: 10.1109/TPAMI.2021.3086140 ]

• DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths.
  Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan Zeng, Yuan Yao
  Thirty-seventh International Conference on Machine Learning (ICML), July 12-18, 2020.
  [ arXiv:2007.02010 ][ early report as arXiv:1905.09449 ][ link ][ GitHub ]

• Differentially Private Federated Learning with Laplacian Smoothing.
  Zhicong Liang, Bao Wang, Quanquan Gu, Stanley Osher, Yuan Yao.
  Applied and Computational Harmonic Analysis, 2024, 72:101660. Short report appeared in NeurIPS Workshop on Federated Learning for Data Privacy and Confidentiality, Vancouver, Canada, Dec. 8-14, 2019.
  [ arXiv:2005.00218 ][ GitHub ][ DOI: https://doi.org/10.1016/j.acha.2024.101660 ]

• Learning the mapping $x\mapsto \sum_{i=1}^d x_i^2$: the cost of finding the needle in a haystack.
  Jiefu Zhang, Leonardo Zepeda-Núñez, Yuan Yao, Lin Lin.
  Communications on Applied Mathematics and Computation, 3, 313-335 (2021).
  [ arXiv:2002.10561 ][ https://doi.org/10.1007/s42967-020-00078-2 ]

• Who Likes What? – SplitLBI in Exploring Preferential Diversity of Ratings.
  Qianqian Xu, Jiechao Xiong, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao.
  AAAI Conference on Artificial Intelligence (AAAI), New York, Feb 7-12, 2020.
  [ DOI: https://doi.org/10.1609/aaai.v34i01.5359 ][ code ]

• Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.
  Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou.
  AAAI Conference on Artificial Intelligence (AAAI), New York, Feb 7-12, 2020.
  [ arXiv:1910.02249 ]

• iSplit LBI: Individualized Partial Ranking with Ties via Split LBI.
  Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang and Yuan Yao.
  Annual Conference on Neural Information Processing Systems (NeurIPS), Vancuver, Canada, 3896–3906, 2019.
  [ pdf ][ code ][ poster ]

• Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size.
  Ke Ma, Jinshan Zeng, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu and Yuan Yao.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), June 2021, 33(6): 2467-2478. Extended from AAAI'18 version.
  [ 10.1109/TKDE.2019.2956700 ]

• $S^2$-LBI: Stochastic Split Linearized Bregman Iterations for Parsimonious Deep Learning.
  Yanwei Fu, Donghao Li, Xinwei Sun, Shun Zhang, Yizhou Wang, and Yuan Yao.
  [ arXiv:1904.10873 ][ GitHub ]

• Deep Robust Subjective Visual Property Prediction in Crowdsourcing.
  Qianqian Xu, Zhiyong Yang, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang, Yuan Yao.
  Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, June 16-20, 2019
  [ arXiv:1903.03956 ][ GitHub source ]

• Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective.
  Chao Gao, Yuan Yao, Weizhi Zhu.
  Journal of Machine Learning Research, 21(160):1-48, 2020.
  [ arXiv:1903.01944 ][ link ][ Github Source ]

• On Global Linear Convergence in Stochastic Nonconvex Optimization for Semidefinite Programming.
  Jinshan Zeng, Ke Ma, Yuan Yao.
  IEEE Transactions on Signal Processing, Vol. 67, No. 16, Page: 4261 - 4275, August 15, 2019.
  [ DOI: 10.1109/TSP.2019.2925609 ][ 2020 ICCM Distinguished Paper Award ]

• On ADMM in Deep Learning: Convergence and Saturation-Avoidance.
  Jinshan Zeng, Shao-Bo Lin, Yuan Yao, Ding-Xuan Zhou.
  Journal of Machine Learning Research, 22(199): 1-67, 2021.
  [ arXiv:1902.02060 ][ link ][ GitHub 1][ GitHub 2]

• Zero-Shot Learning via Recurrent Knowledge Transfer.
  Bo Zhao, Xinwei Sun, Xiaopeng Hong, Yuan Yao, and Yizhou Wang.
  2019 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Village, HI, USA, 7-11 Jan. 2019.
  [ DOI: 10.1109/WACV.2019.00144 ] [ GitHub source ]

• Rethinking Breiman's Dilemma in Neural Networks: Phase Transitions of Margin Dynamics.
  Weizhi Zhu, Yifei Huang, Yuan Yao.
  Frontiers in Applied Mathematics and Statistics, special section on Mathematics of Computation and Data Science, 30 October 2020. This work was presented at ICCM'2019 in Beijing, which appeared in Annals of Mathematical Sciences and Applications, Volume 7, Number 2, pages: 221-258, 2022.
  [ arXiv:1810.03389 ][ DOI:10.3389/fams.2020.575073 ][ DOI: https://dx.doi.org/10.4310/AMSA.2022.v7.n2.a4 ]

• Robust Estimation and Generative Adversarial Networks.
  Chao Gao, Jiyi Liu, Yuan Yao, Weizhi Zhu.
  International Conference on Learning Representations (ICLR), New Orleans, Louisiana, United States, May 6 - May 9, 2019.
  [ arXiv:1810.02030 ][ ICLR'19 ][ GitHub source ]

• Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification.
  Yin Xian, Hanlin Gu, Wei Wang, Xuhui Huang, Yuan Yao, Yang Wang, Jian-Feng Cai.
  The 6th IEEE Global Conference on Signal and Information Processing, Anaheim, California, Nov 26-29, 2018.
  [ arXiv:1810.08829 ] [ GitHub source ]

• A Margin-based MLE for Crowdsourced Partial Ranking.
  Qianqian Xu, Jiechao Xiong, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan Yao.
  In 2018 ACM Multimedia Conference (MM’18), October 22–26, 2018, Seoul, Republic of Korea. ACM, New York, NY, USA.
  [ arXiv:1807.11014 ]

• FDR-HS: An Empirical Bayesian Identification of Heterogenous Features in Neuroimage Analysis
  Xinwei Sun, Lingjing Hu, Fandong Zhang, Yuan Yao, Yizhou Wang
  The 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, Spain, 2018
  [ arXiv:1807.08125 ]

• MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
  Bo Zhao, Xinwei Sun, Yanwei Fu, Yuan Yao, Yizhou Wang
  The 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018
  [ arXiv:1806.04360 ] [ link ][ GitHub source1 ][ GitHub source2]

• From Social to Individuals: a Parsimonious Path of Multi-level Models for Crowdsourced Preference Aggregation
  Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Qingming Huang, Yuan Yao
  IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(4):844-856, 2019. Extended from MM'16 in [ arXiv:1607.03401 ].
  [ arXiv:1804.11177 ] [ doi: 10.1109/TPAMI.2018.2817205 ][ GitHub source]

• A Proximal Block Coordinate Descent Algorithm for Deep Neural Network Training
  Tim Tsz-Kit Lau, Jinshan Zeng, Baoyuan Wu, Yuan Yao
  The 6th International Conference on Learning Representations (ICLR 2018), Workshop Track
  [ arXiv:1803.09082 ]

• Global Convergence of Block Coordinate Descent in Deep Learning
  Jinshan Zeng, Tim Tsz-Kit Lau, Shaobo Lin, Yuan Yao
  The 36th International Conference on Machine Learning (ICML), Long Beach, California, June 10-15, 2019.
  [ arXiv:1803.00225 ]

• Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction
  Jinshan Zeng, Ke Ma, Yuan Yao
  Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarote, Spain, 2018.
  [ arXiv:1802.06232 ] [ link ]

• A Unified Dynamic Approach to Sparse Model Selection.
  Chendi Huang, Yuan Yao.
  Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), Lanzarote, Spain, 2018.
  [ arXiv:1810.03608 ] [ link ]

• Stochastic Non-Convex Ordinal Embedding with Stabilized Barzilai-Borwein Step Size
  Ke Ma, Jinshan ZENG, Jiechao Xiong, Qianqian Xu, Xiaochun Cao, Wei Liu, Yuan Yao
  The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Louisiana, Feb 2-7, 2018.
  [ arXiv:1711.06446 ] [ GitHub Source in Matlab ]

• HodgeRank with Information Maximization for Crowdsourced Pairwise Ranking Aggregation
  Qianqian Xu, Jiechao Xiong, Xi Chen, Qingming Huang, Yuan Yao
  The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Louisiana, Feb 2-7, 2018.
  [ arXiv:1711.05957 ] [ GitHub ]

• Accelerated Block Coordinate Proximal Gradients with Applications in High Dimensional Statistics
  Tsz Kit Lau and Yuan Yao
  The 10th NIPS Workshop on Optimization for Machine Learning (NIPS 2017), Long Beach, California, Dec 3-8, 2017.
  [ arXiv:1710.05338 ]

• Exploring Outliers in Crowdsourced Ranking for QoE
  Qianqian Xu, Ming Yan, Chendi Huang, Jiechao Xiong, Qingming Huang, and Yuan Yao
  ACM Multimedia 2017 (Oral presentation), Mountain View, California, Oct 23-27, 2017.
  [ arXiv:1707.07539 ]

• GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction
  Xinwei Sun, Lingjing Hu, Yuan Yao, and Yizhou Wang
  Medical Image Computing and Computer Assisted Interventions Conference (MICCAI), Quebec City, Canada, Sept 10-14, 2017.
  [ arXiv:1705.09249 ]

• Boosting with Structural Sparsity: A Differential Inclusion Approach
  Chendi Huang, Xinwei Sun, Jiechao Xiong, and Yuan Yao
  Applied and Computational Harmonic Analysis, 48(1): 1-45, 2020.
  [ arXiv:1704.04833 ] [ https://doi.org/10.1016/j.acha.2017.12.004 ]

• A Statistical Learning Approach for Drug Sensitivity Prediction with Cancer Cell Line Data
  Lijing Wang, Yangzhong Tang, Stevan Djakovic, Julie Rice, Tony Wu, Daniel J. Anderson, and Yuan Yao
  Dahshu 2017: Data Science and Computational Precision Health, San Francisco, Feb 20-22, 2017.
  [ Poster ][ Dataset Released in Kaggle ]

• Split LBI: An Iterative Regularization Path with Structural Sparsity
  Chendi Huang, Xinwei Sun, Jiechao Xiong, Yuan Yao
  Advances in Neural Information Processing Systems 29 (NIPS 2016), Barcelona, Spain, December 5-10, 2016.
  [ NIPS link ] [ Matlab codes at GitHub ]

• Learning rates of regression with q-norm loss and threshold
  Ting Hu, Yuan Yao
  Analysis and Applications, Volume 14, Issue 06, November 2016.
  [ DOI ]

• Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation
  Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan Yao
  ACM Multimedia Conference (ACMMM), Amsterdam, Netherlands, October 15-19, 2016.
  [ arXiv:1607.03401 ] [ pdf ]

• False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking
  Qianqian Xu, Jiechao Xiong, Xiaochun Cao, Yuan Yao
  Proceedings of The 33rd International Conference on Machine Learning (ICML), New York, June 19-24, 2016.
  [ arXiv:1605.05860 ] [ pdf ] [ supplementary ]

• A Tutorial on Libra: R package for the Linearized Bregman Algorithm in high dimensional statistics
  Jiechao Xiong, Feng Ruan, and Yuan Yao
  Handbook of Big Data Analytics, Ed. by Hardle, Lu and Shen, page 425 - 453, [ DOI: https://doi.org/10.1007/978-3-319-18284-1 ], Springer, 2018
  [ PDF in Chinese ] [ PDF in English ] [ arXiv ] [ Cran R website ] [ link ]

• Mixed and missing data: a unified treatment with latent graphical models
  Xiao Li, Jinzhu Jia, and Yuan Yao
  [ arXiv:1511.04656 ]

• Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications
  Qing Wang, Hengshu Zhu, Wei Hu, Zhiyong Shen, and Yuan Yao
  ACM SIGKDD, Sydney, Australia, August 10-13, 2015.
  [ pdf ] [ Demo @Baidu-BDL]

• Analysis of Crowdsourced Sampling Strategies for HodgeRank with Sparse Random Graphs
  Braxton Osting, Jiechao Xiong, Qianqian Xu, and Yuan Yao
  Applied and Computational Harmonic Analysis, 41 (2): 540-560, 2016
  [ arXiv:1503.00164 ] [ ACHA online ] [Matlab codes to reproduce our results]

• Robust Subjective Visual Property Prediction from Crowdsourced Pairwise Labels
  Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Jiechao Xiong, Shaogang Gong, Yizhou Wang, and Yuan Yao
  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol.38, no.3, pp. 563-577, March 2016.
  [ arXiv:1501.06202 ] [ doi:10.1109/TPAMI.2015.2456887 ]

• Fast Adaptive Least Trimmed Squares for Robust Evaluation of Quality of Experience.
  Qianqian Xu, Ming Yan, and Yuan Yao
  [ arXiv:1407.7636 ] [Matlab in Google code]

• Geometric Tight Frame based Stylometry for Art Authentication of van Gogh Paintings
  Haixia Liu, Raymond H. Chan, and Yuan Yao
  Applied and Computational Harmonic Analysis, 41(2): 590-602, 2016
  [pdf] [arXiv:1407.0439] [ ACHA online Dec 2, 2015 ]

• Sparse Recovery via Differential Inclusions
  Stanley Osher, Feng Ruan, Jiechao Xiong, Yuan Yao and Wotao Yin
  Applied and Computational Harmonic Analysis, 41(2):436-469, 2016
  [pdf] [ arXiv:1406.7728 ] [ ACHA online January 14, 2016 ] [ R package: Libra ]

• Interestingness Prediction by Robust Learning to Rank.
  Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong, and Yuan Yao
  13th European Conference on Computer Vision (ECCV), Zurich, Switzerland, Sep 8-12, 2014.
  [pdf]

• Online Learning as Stochastic Approximations of Regularization Paths: Optimality and Almost-sure Convergence.
  Pierre Tarres and Yuan Yao.
  IEEE Transactions on Information Theory , 60(9):5716-5735, 2014.
  short report appeared in Mathematisches Forschungsinstitut Oberwolfach, Report 30/2008, Learning Theory and Approximation.
  [pdf] [Oberwolfach Report][arXiv.org:1103.5538]

• Online HodgeRank on Random Graphs for Crowdsourceable QoE Evaluation.
  Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao
  IEEE Transactions on Multimedia, 16(2):373-386, Feb. 2014.
  [pdf]

• Robust Evaluation for Quality of Experience in Crowdsourcing.
  Qianqian Xu, Jiechao Xiong, Qingming Huang, and Yuan Yao
  ACM Multimedia 2013.
  [pdf]

• Hierarchical Nystrom Methods for Constructing Markov State Models for Conformational Dynamics.
  Yuan Yao, Raymond Z. Cui, Gregory R. Bowman, Daniel Silva, Jian Sun, Xuhui Huang
  The Journal of chemical physics 2013 May 7, 138 (17):174106. arXiv:1301.0974, 2013

• The Landscape of Complex Networks: Critical Nodes and A Hierarchical Decomposition.
  Weinan E, Jianfeng Lu, and Yuan Yao.
  Methods and Applications of Analysis, special issue in honor of Professor Stanley Osher on his 70th birthday, 20(4):383-404, 2013.
  [ pdf ] [arXiv:1204.6376]

• Online Crowdsourcing Subjective Image Quality Assessment.
  Qianqian Xu, Qingming Huang, and Yuan Yao.
  ACM Multimedia 2012.
  [pdf]

• HodgeRank on Random Graphs for Subjective Video Quality Assessment.
  Qianqian Xu, Qingming Huang, Tingting Jiang, Bowei Yan, Weisi Lin, and Yuan Yao.
  IEEE Transactions on Multimedia, 14(3):844-857, 2012
  [pdf][ Matlab codes in zip ]

• Compressive Network Analysis.
  Xiaoye Jiang, Yuan Yao, Han Liu, and Leo Guibas
  IEEE Transactions on Automatic Control, 59(16): preprint, 2014
  [ arXiv:1104.4605 ][DOI: 10.1109/TAC.2014.2351712 ]

• Detecting Network Cliques with Radon Basis Pursuit.
  Xiaoye Jiang, Yuan Yao, Han Liu, and Leo Guibas
  AISTATS 2012.
  [pdf]

• Random Partial Paired Comparison for Subjective Video Quality Assessment via HodgeRank.
  Qianqian Xu, Tingting Jiang, Yuan Yao, Qingming Huang, Bowei Yan, Weisi Lin.
  ACM Multimedia 2011.
  [pdf]

• Simulating Human Saccadic Scanpaths on Natural Images.
  Wei Wang, Cheng Chen, Yizhou Wang, Tingting Jiang, Fang Fang, Yuan Yao.
  IEEE Computer Vision and Pattern Recognition (CVPR) 2011.
  [pdf]

• Overcomplete Radon Bases for Target Property Management in Sensor Networks.
  Xiaoye Jiang, Mo Li, Yuan Yao, and Leonidas Guibas.
  The 10th International Conference on Information Processing in Sensor Networks, Chicago, (ACM IPSN) 2011.
  [pdf]

• Hodge Decomposition of Paired Comparison Flows in Click-through Data.
  Zhanglong Ji, Yang An, Ying Chen, Yuan Yao, Jun Xu, and Hang Li.
  Tech Report, appeared in The 6th Joint Workshop on Machine Perception and Robotics (MPR), Fukuoka, Japan, 2010.
  [pdf]

• Statistical Ranking and Combinatorial Hodge Theory.
  Xiaoye Jiang, Lek-Heng Lim, Yuan Yao and Yinyu Ye.
  Mathematical Programming, Volume 127, Number 1, Pages 203-244, 2011.
  [pdf][ arxiv.org/abs/0811.1067][ Matlab Codes]

• On Complexity Issues of Online Learning Algorithms.
  Yuan Yao.
  IEEE Transactions on Information Theory, 56(12): 6470 - 6481, 2010.
  [pdf]

• Constructing Multi-Resolution Markov State Models (MSMS) to Elucidate RNA Hairpin Folding Mechanisms.
  Huang, X., Y. Yao, J. Sun, L. Guibas, G. Carlsson and V.S. Pande.
  Proceedings of the Pacific Symposium on Biocomputing, 15, 228-239, (2010)
  [pdf online]

• Stable Identification of Cliques with Radon Basis Pursuit.
  Xiaoye Jiang, Yuan Yao, and Leonidas Guibas.
  preprint.
  [pdf]

• A Fast Geometric Clustering Method on Conformation Space of Biomolecules.
  Jian Sun, Yuan Yao, Xuhui Huang, Vijay Pande, Gunnar Carlsson, and Leonidas Guibas.
  preprint.
  [pdf]

• Topological Methods for Exploring Low-density States in Biomolecular Folding Pathways.
  Yuan Yao, Jian Sun, Xuhui Huang, Gregory Bowman, Gurjeet Singh, Michael Lesnick, Vijay Pande, Leonidas Guibas and Gunnar Carlsson.
  J. Chem. Phys. 130, 144115 (2009).
  [pdf][Online Publication][SimTK Link: Data and Matlab Codes] [Selected by Virtual Journal of Biological Physics Research, 04/15/2009].

• Metric Learning for Phylogenetic Invariants: An Algebraic Approach to Evolutionary Tree Construction.
  Eriksson, Nick and Yuan Yao.
  Journal of Chinese Linguistics, special issue on New Horizons in Evolutionary Linguistics, ed. by PENG Gang and WANG Feng, Monograph No. 27, page: 67-85, 2017.
  [early version: arxiv.org/abs/q-bio/0703034].

• Structural insight into RNA hairpin folding intermediates.
  Bowman, Gregory R., Xuhui Huang, Yuan Yao, Jian Sun, Gunnar Carlsson, Leonidas Guibas and Vijay Pande.
  Journal of American Chemistry Society, 2008, 130 (30): 9676-9678.
  [ pdf ][link]

• On Early Stopping in Gradient Descent Learning.
  Yuan Yao, Lorenzo Rosasco and Andrea Caponnetto.
  Constructive Approximation, 2007, 26 (2): 289-315.
  [report][pdf][ link ]

• Cross-Validation Based Adaptation for Regularization Operators in Learning Theory
  Andrea Caponnetto and Yuan Yao.
  CBCL Paper \#265/AI Technical Report \#063, Massachusetts Institute of Technology, Cambridge, MA, September, 2006.
  Analysis and Applications vol. 08, no. 02, pp. 161-183, 2010
  [ https://doi.org/10.1142/S0219530510001564 ][ MIT Tech-Report ]

• Mercer's Theorem, Feature Maps, and Smoothness
  Ha Quang Minh, Partha Niyogi and Yuan Yao.
  In Proc. of Computational Learning Theory (COLT), 2006.
  [pdf]

• Online Learning Algorithms.
  Steve Smale and Yuan Yao.
  Foundations of Computational Mathematics. 2006, 6 (2): 145-170.
  [pdf]

• Combining Flat and Structured Representations for Fingerprint Classification with Recursive Neural Networks and Support Vector Machines.
  Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil, Paolo Frasconi, and Fablio Roli.
  Pattern Recognition, 36(2): 397-406, 2003.
  [ pdf ] [ link ]

• A New Machine Learning Approach to Fingerprint Classification.
  Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil, Paolo Frasconi, and Fablio Roli.
  In: AI*IA 2001: Advances in Artificial Intelligence, LNCS, vol.2175: 57-63.
  [ pdf ]

• Fingerprint Classification with Combinations of Support Vector Machines.
  Yuan Yao, Massimiliano Pontil and Fablio Roli.
  In: Proceedings of Audio- and Video-Based Biometric Person Authentication, Third International Conference, AVBPA 2001: 253-258.
  [ link ]

• Multiscale Morphology for Color Images Implemented by Fuzzy Cellular Neural Network.
  Yuan Yao, Xiaofeng Zhang, Tianwen Zhang and Guangxiong Wang.
  In: Proceedings of IEEE Hong Kong Symposium on Robotics and Control, July 1999, Hong Kong, pp. 459-462.

• Morphological Reconstruction for Color Images Implemented by Fuzzy Cellular Neural Networks.
  Yuan Yao, Guangxiong Wang and Tianwen Zhang.
  Chinese Journal of Computers (in Chinese), 22(7): 727-732, 1999.
  [pdf][ link ]

• Application of Fuzzy Cellular Neural Networks to Stone Inscription Reconstruction in Chinese Calligraphy.
  Yuan Yao, Guangxiong Wang and Tianwen Zhang.
  Journal of Computer Research and Development (in Chinese), 36(3): 282-286, 1999.
  [pdf]

• Global Optimal Robust Controller Design.
  Lianfeng Li, Guangxiong Wang and Yuan Yao.
  Journal of Control Theory and Applications (in Chinese), 18(2): 266-269, 2001.

• On the Application Problem of the Gap Metric for SISO Systems.
  Yuan Yao, Lianfeng Li and Gejun Bao.
  Journal of Harbin Institute of Technology (in Chinese), 31(6): 19-21, 1999.
  [pdf]

• Optimal Robust Performance in Constantly Scaled H_infinity control.
  Yuan Yao, Jingbo Wang, Lianfeng Li and Guangxiong Wang.
  In: Korea-China Process System Engineering Workshop. August 1999, Korea.

• Robust Gain-scheduled H_infinity control with Constant Diagonal Scaling.
  Yuan Yao, Lianfeng Li, Guangxiong Wang and Jingbo Wang.
  In: Proceedings of IEEE Hong Kong Symposium on Robotics and Control, July 1999, Hong Kong, pp. 628-632.

• Application of Quadratic Stabilization, Constantly Scaled H_infinity control and mu-Synthesis.
  Xiaofeng Wang, Yuan Yao, Guangxiong Wang and Jingbo Wang.
  In: Proceedings of IEEE Hong Kong Symposium on Robotics and Control, July 1999, Hong Kong, pp. 633-637.

• Identifying Noise Model in Closed-Loop Using Subspace Method.
  Jingbo Wang, Jibril Jiya, Tianyou Chai, Yuan Yao, Guangxiong Wang and Shijie Xu.
  In: Proceedings of the IEEE International Vehicle Electronics Conference (IVEC '99), September 6-9, 1999, Changchun, China, pp. 349-351.

• FEM-Based Modeling in Servo Design.
  Yuan Yao and Jing Luo.
  Electric Machine and Control (in Chinese), 2(2): 108-111, 1998.

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