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

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.

Recent Papers and Preprint

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

• Learning to Rank with Combinatorial Hodge Theory.
  Xiaoye Jiang, Lek-Heng Lim, Yuan Yao and Yinyu Ye.
  submitted to Mathematical Programming.
  [Abstract][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.
  submitted to PLoS Computational Biology.
  [Abstract][pdf][SimTK Link: Data and Matlab Codes].

• Online Learning as Stochastic Approximations of Regularization Paths.
  Pierre Tarres and Yuan Yao.
  short report appeared in Mathematisches Forschungsinstitut Oberwolfach, Report 30/2008, Learning Theory and Approximation.
  [Oberwolfach Report][pdf]

• Metric Learning for Phylogenetic Invariants.
  Eriksson, Nick and Yuan Yao.
  preprint.
  [arxiv.org/abs/q-bio/0703034].

• On Complexity Issue of Online Learning Algorithms.
  Yuan Yao.
  IEEE Transactions on Information Theory, Accepted.
  [pdf]

• 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.
  [link]

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

• 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.
  [pdf link]

• 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]

Papers in Computer Vision, Machine Learning and Pattern Recognition

• 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]

• 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.
  [pdf]

• 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.

• 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.

Papers in System and Control

• 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.

• 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.

Conference Talks/Poster Presentations

• Yao, Y., J. Sun, X. Huang, V. Pande, L. Guibas and G. Carlsson (2008). Topological Methods for Exploring Biomolecular Folding Pathways, the 9th Biomedical Computation at Stanford (BCATS), spotlight poster presentation, October 26, 2008, Stanford, CA.

• Sun, J., X. Huang, Y. Yao, G. Carlsson, V. Pande and L. Guibas (2008). A Well-controlled Fast Clustering Method on Conformation Space of Biomolecules, the 9th Biomedical Computation at Stanford (BCATS), poster presentation, October 26, 2008, Stanford, CA.

• Bowman, G.~R., X. Huang, Y. Yao, J. Sun and V. Pande (2008). Adaptive Seeding: A New Method for Simulating Biologically Relevant Timescales, the 9th Biomedical Computation at Stanford (BCATS), poster presentation, Stanford, October 26, 2008.

• Combinatorial Hodge Theory and A Geometric Approach to Ranking, SIAM Annual Meeting, minisymposium: Mathematical Methods in Data Mining, San Diego, July 7-11, 2008.

• Topological Methods for Exploring Low-density States in Biomolecular Folding Pathways, Modern Massive Data Sets (MMDS), Stanford, June 25-39, 2008.

• Hodge Decomposition, Spectral Embedding, and the Netflix Dataset, Bay Area Scientific Computing Day: honoring Professors Kahan and Parlett, MSRI, Berkeley, March 29-30, 2008.

• Scheler, G. and Y. Yao (2007). Equilibria in neuroadaptive pathways. RECOMB Systems Biology, poster presentation, Dec 1-2, 2007, La Jolla, CA.

• Hodge Theory and Rank Aggregation, Computational Applications of Algebraic Topology, I, AMS sectional meeting, Albuquerque, New Mexico, October 13, 2007.

• Combinatorial Laplacians and Rank Aggregation, the 6th International Congress of Industrial and Applied Mathematics (ICIAM), minisymposium: Novel Matrix Methods for Internet Data Mining. Zurich, Switzerland, July 16-20, 2007.

• Topology Learning of High Dimensional Probability Density Functions, the 1st International Congress of IPIA, Conference on Applied Inverse Problems, minisymposium: Learning from Examples as an Inverse Problem, PIMS, University of British Columbia, Vancouver, Canada, June 25-29, 2007.

• Metric Learning for Phylogenetic Invariants, Student Algebraic Statistics Seminar, University of California at Berkeley, Feb. 5, 2007.

• Yuan Yao and Jinyun Ke (2000). Exploring Semantic Complexity by Computational Learning Theory. Evolutionary Computation and Cognitive Science (ECCS'2000) Workshop, poster presentation. January, 2000, Melbourne, Australia.

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