Invited Presentations (Colloquia, Workshops, Plenary Talks)

• Data clustering: a subspace-matching point of view and K-scalable algorithms. Chongqing University. Chongqing, China. Mar. 28, 2019.

• Data clustering: a subspace-matching point of view and K-scalable algorithms. School of Mathematical Sciences, UESTC. Chengdu, China. Mar. 27, 2019.

• Data clustering: subspace-based models and a high-performance algorithm. The Greater Bay Area Computational Optimization Workshop. The Hong Kong Polytechnic University. Hong Kong, China. Jan. 23-24, 2019.

• Data Clustering: A New Algorithm Based on Subspace Matching. 2018 International Conference on Data Science. Fudan University. Shanghai, China. Dec. 18, 2018.

• On Local Convergence of ADMM-like Methods for Equality Constrained Optimization. 2018 Workshop on New Computing-Driven Opportunities for Optimization August 12-18, 2018. Wuyi, Fujian, China.

• Local Convergence of ADMM-like Methods for Equality Constrained Optimization. CUHK(SZ) Workshop on Optimization Theory and Applications. August 9-10, 2018. Shenzhen, China.

• A New Algorithm for Data clustering: K-indicators versus K-means. Workshop on New Optimization Methods. The Hong Kong Polytechnic University. Nov. 20, 2017. Hong Kong, China

• Big-data Clustering: K-means vs K-indicators. 2016 International Workshop on Mathematical Issues in Information Sciences (MIIS). Dec. 19th, 2016. Shenzhen, China

• Big-data Clustering: K-means vs K-indicators. CAAM Colloquium, Rice University. October 31, 2016.

• Towards higher quality and faster speed in large-scale K-means clustering. 2016 Workshop on Modern Optimization and Applications. June 27th, 2016. Beijing, China

• Accelerating convergence by augmented Rayleigh-Ritz projections for eigenpair computation. Workshop on Optimization & Eigenvalue Computation, , organized by Beijing International Center of Mathematics Research (BICMR), Peking University. June 25, 2016. Beijing, China.

• Block algorithms in an augmented Rayleigh-Ritz framework for large-scale exterior eigenpair computation. Sparse days in St Girons III, Saint Girons, France. June 29th - July 2nd, 2015.

• A New Approach to Solving the K-Means Clustering Problem. LSEC/NCMIS, Chinese Academy of Sciences. Beijing, China. June 18th, 2015.

• Block algorithms with augmented Rayleigh-Ritz projections for large-scale eigenpair computation. School of Mathematic. Chongqing University. Chongqing, China. June 16, 2015.

• Block algorithms with augmented Rayleigh-Ritz projections for large-scale eigenpair computation. Applied Math Seminar. University of California Davis. May 21, 2015.

• A Gauss-Newton method for low-rank matrix approximations. Department of Computational and Applied Mathematics, Rice University. March 17, 2014.

• An Efficient Gauss-Newton Algorithm for Symmetric Low-Rank Product Matrix Approximations. Institute of Computational Mathematics, Chinese Academy of Sciences. Beijing, China. June 3, 2014.

• An SOR Algorithm for Low-Rank Matrix Completion. Beijing International Center of Mathematics Research (BICMR). Peking University. Beijing, China. June 4, 2014.

• An Efficient Gauss-Newton Algorithm for Symmetric Low-Rank Product Matrix Approximations. Department of Mathematics. Chongqing University, Chongqing. China. June 12, 2014.

• An SOR Algorithm for Low-Rank Matrix Completion. Department of Mathematics. University of Electronic Science and Technology of China. Chengdu, China. June 20, 2014

• A Penalty-based Trace Minimization Method for Large-scale Eigenspace Computation. College of Mathematics and Statistics, Chongqing University. December 6th, 2012. Chongqing, China

• Towards a Massively Parallel Algorithm for Large-Scale Eigenspace Computation.
  Institute of Computational Mathematics, Chinese Academy of Sciences. Beijing, China. June 22, 2012.

• Compressive Sensing: A Non-RIP Analysis. College of Mathematics and Statistics,
  Chongqing University. June 19, 2012. Chongqing, China

• A Non-RIP Theory for Compressive Sensing via L1-Minimization. International Symposium on Compressed Sensing: Theory and Applications (plenary speaker). Tianjin University. Tianjin, China, June 9th-12th, 2012.

• A Non-RIP Theory for Compressive Sensing. A 3-lecture series at Institute of Computational Mathematics, Chinese Academy of Sciences, Beijing, China. May 25th - June 4th, 2012.

• Factorization-based algorithms for low-rank matrix completion and approximations. Institute of Computational Mathematics, Chinese Academy of Sciences, Beijing, China, December 13, 2011

• Factorization-based algorithms for low-rank matrix completion and approximations. Department of Mathematics, Beijing Jiaotong University, Beijing, China, December 12, 2011

• Compressive Sensing: A Brief Introduction. Department of Mathematics, Shanghai University, Shanghai, China, Nov. 25, 2011.

• Hyperspectral image compressive sensing and unmixing. Department of Mathematics, Shanghai Jiao Tong University, Shanghai, China, Nov. 23, 2011.

• Compressive Sensing: A Brief Introduction. Department of Mathematics, Zhejiang University, Hangzhou, China, Nov. 21, 2011.

• An Efficient SVD Algorithm for Large Unstructured Matrices. Workshop on Optimization in Material Computing (invited speaker). Institute of Computational Mathematics, Chinese Academy of Sciences, Beijing, Nov. 16th, 2011.

• Compressive Sensing: A Brief Introduction. Dept. of Mathematics, Shanghai Jiao Tong University, Shanghai, China, Nov. 14, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. University of Science and Technology of China, Hefei, China, October 31, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. Dept. of Mathematics, Shanghai Jiao Tong University, Shanghai, China, October 26, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. The 5th Sino-Japanese Optimization Meeting (plenary speaker), Beijing, China, September 28, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. School of Mathematical Sciences, Peking University, Beijing, China, Sept. 16, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. School of Mathematical Sciences, Dalian University of Technology, Dalian, China, Sept. 13, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. Institute of Computational Mathematics, Chinese Academy of Sciences, Beijing, China, September 6th, 2011.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. Department of CAAM, Rice University. Houston, Texas. November 8, 2010.

• Some Recent Advances in Alternating Direction Methods: Practice and Theory. Department of Mathematics, University of Texas. Austin, Texas. October 29, 2010.

• Recent Advances in Alternating Direction Methods: Theory and Practice. IPAM Workshop: Numerical Methods for Continuous Optimization. UCLA. Los Angeles, California. October 11, 2010.

• Hyperspectral Image Compressive Sensing and Unmixing. 2012 Conference of LSEC Center for Optimization and Applications, Chinese Academy of Sciences. Lang-Ya Mountain, Hebei, China. June 23, 2011.

• An SOR Algorithm for Matrix Completion (with Zaiwen Wen and Wotao Yin). International Workshop on Large Scale Optimization: Analysis, Algorithm and Applications. Fudan University, Shanghai, China. May 20, 2010.

• Sparsity Regularizations and Augmented Lagrangian Alternating Direction Methods. Department of Mathematics, Nanjing University, Nanjing, China. May 17, 2010.

• Sparsity Regularizations and Augmented Lagrangian Alternating Direction Methods. The School of Electronic Engineering, Xidian University, Xian, China. May 14, 2010.

• Sparsity regularizations and augmented Lagrangian alternating direction methods. Workshop on Inverse Problems: Theory, Computation, and Applications. Michigan State University. April. 19-20, 2010.

• Sparse Solution Recovery via L1 or TV Minimization: Theory, Models, and Algorithms. Plenary Speaker at International Conference on Numerical Linear Algebra and Optimization. Lijiang, China. August 16-18, 2009.

• Compressive Sensing: RIP-free Theory and Some Efficient Algorithms. Invited Speaker at Conference on Optimization Applications in Engineering and Applied Sciences. University of Illinois at Urbana-Champaign, March 26-28, 2009.

• Sparse Solution Recovery via L1-minimization: Theory, Models, and Algorithms. School of Mathematics at the University of Edinburgh. July 10, 2009.

• Compressive Sensing via L1-minimization: Theory, Models, and Algorithms. Department of Electrical and Electronic Engineering, Imperial College of London. July 06, 2009.

• Sparse Solution Recovery via L1-minimization: Theory, Models, and Algorithms. Institute of Mathematics, University of Graz, July 1, 2009.

• Sparse Solution Recovery via L1-minimization: Theory, Models, and Algorithms. Institute of Mathematics, University of Wurzburg, June 26, 2009.

• Compressive Sensing: Theory, Models and Algorithms. ECE Department, University of Minnesota June 11, 2009

• Compressive Sensing: RIP-free Theory and Efficient Algorithms. Department of Mathematics, UC Irvin, May 4, 2009.

• Compressive Sensing Theory and L1-related Optimization Algorithms. Department of Computational and Applied Mathematics, Rice University. January 26, 2009.

• Acquiring less data without losing content: Compressive Sensing Theory and Algorithms. The First International Conference on Frontiers in Computational Mathematics. Invited Speaker. Guilin, China, December 15-17, 2008.

• Compressive Sensing Theory and Algorithms. Institute of Electronics, Chinese Academy of Sciences. December 5, 2008.

• A class of fast algorithms for TV-based Image Reconstruction. Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of Sciences. December 4, 2008.

• Acquiring Less Data Without Losing Content: Compressive Sensing Theory and Algorithms. Invited speaker. DTRA-NSF 2008 Algorithm Workshop. Baltimore, Maryland, November 4-6,2008.

• Enhanced Compressive Sensing and More. Invited one-hour talk Speaker, Workshop on Nonlinear Approximation Techniques Using L1, Texas A & M University, May 16th, 2008.

• Large-Scale L1-Related Minimization in Compressive Sensing and Beyond. Colloquium, Department Mathematics, Arizona State University. March 5th, 2008.

• A Fixed-Point Continuation Method for $\ell_1$-Regularized Minimization with Application to Compressed Sensing (with Elaine Hale and Wotao Yin). 2007 von Neumann Symposium on Sparse Representation and High-Dimensional Geometry. Snowbird Utah July 8-12, 2007.

• Solution Recovery via L1 minimization: What are possible and Why? Eighth US-Mexico Workshop on Optimization and its Applications Huatulco, Mexico, January 8 - 12, 2007.

• An approach to optimal cancer radiation treatment planning. Invited talk at the Annual Meeting of the Chongqing Society of Industrial and Applied Mathematics. June 17th, 2006.

• Hilbert's 17th problem, EDP and conic programming. Collage of Mathematics and Sciences, Chongqing University. June 14th, 2006.

• Hilbert's 17th problem, SDP and conic programming. Department of Mathematics, Chongqing Normal University. June 12th, 2006.

• Solution recovery for non-square systems via L1 minimization. Invited Lecture at the International Conference on Nonlinear Programming with Applications, Shanghai, China. May 29th, 2006.

• Sparse solution recovery by L1-minimization. Special Session on New Developments in Optimization. 2006 Spring Central Sectional Meeting, Notre Dame, IN, April 8-9, 2006.

• A General Robust-optimization Framework for Nonlinear Optimization. Workshop On Large-Scale Robust Optimization. Santa Fe, New Mexico, August 31 - September 2, 2005.

• A Robust optimization formulation for general nonlinear programming. Department of Information Systems and Algorithms, Delft University of Technology. Delft, Netherlands. May 12, 2005.

• Optimization in Action: Help treating cancers. Distinguished Lecture Series. Dept of Industrial Engineering, University of Houston. March 11, 2005.

• Optimization in Action: Help treating cancers. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong. Nov. 17, 2004.

• Optimization in Action: Help treating cancers. Department of Applied Mathematics, Hong Kong Polytechnic University. Oct. 21, 2004.

• A Unified Analysis for a Class of Long-Step Primal-Dual Path-Following Interior-Point Algorithms for Semidefinite Programming (with Monteiro). ICS Prize Tutorial. INFORMS Annual Meeting 2002, San Jose, Nov. 17-20, 2002.

• A Global Optimization Problem in Computational Biology: Molecular Replacement Problem. Thematic Year Optimization Visitors to the Fields Institute, May 13, 2002.

• Hilbert's 17th Problem, SDP and DSP and Some New Applications of SDP. Colloquium, Department of Computational and Applied Mathematics, Rice University. Feb. 11, 2002.

• Interior point methods for mathematical programming. Invited 1.5-hour Tutorial. INFORMS Annual Meeting, Miami Beach, Florida, November 3-7, 2001.

• Interior point methods and semidefinite programming. Scientific Computing Seminar, University of Houston. Feb. 15, 2001. Houston, Texas.

• Interior point methods and semidefinite programming. 2000 SIAM Annual Meeting. Invited Plenary speaker. July 10-14, 2000. Rio Grande, Puerto Rico.

• Solving Semidefinite Programs via Nonlinear Programming. Department of Mathematics, University of California Los Angeles, November 9, 1999.

• Solving Semidefinite Programs via Nonlinear Programming: Transformations and Derivatives. First Workshop on Nonlinear Optimization: "Interior-Point and Filter Methods". Center for Mathematics - University of Coimbra, Portugal. October 27-30, 1999.

• Solving Semidefinite Programs via Nonlinear Programming. Invited plenary lecture, Nanjing International Conference on Optimization and Numerical Linear Algebra. Nanjing, China. Sept. 27-30, 1999.

• Solving Semidefinite Programs via Nonlinear Programming. Part I: Transformations and Derivatives. Department of Computational and Applied Mathematics, Rice University, Sept. 13, 1999.

• An Interior-Point Algorithm for the Max-Volume Ellipsoid Problem. DIMACS Workshop on Semidefinite Programming and its Applications to Large Scale Discrete Optimization. Princeton University. January 7-9, 1999.

• A Unified Analysis for a Class of Primal-Dual Path-Following Algorithms for Semidefinite Programming. Invited Lecture at the International Symposium on Computation and Optimization, Hayama, Kanagawa, Japan, Aug. 12-16, 1996.

• Infeasible Primal-Dual Interior-Point Methods for Semidefinite Programming. Workshop on Semidefinite Programming and Interior-Point Approaches for Combinatorial Optimization Problems. The Fields Institute, Toronto, Canada. May 15-17, 1996.

• Infeasible interior point methods: theory and software. Courant Institute of Mathematics, New York University, Nov. 17, 1995.

• Infeasible interior point methods: theory and software. Invited speaker at the DOE/OSC Mathematics Workshop, Albuquerque, NM. Feb. 29 - Mar. 1, 1995.

• Interior-point methods for linear programming: the state of the art (as an invited plenary speaker). The 1993 Conference on Scientific and Engineering Computing for Young Chinese Scientists, Beijing, China, Aug. 16-21, 1993.

• Convergence of infeasible interior-point methods for the horizontal linear complementarity problem. Center for Applied Mathematics, Cornell University, April 30, 1993.

• Interior point methods for linear and nonlinear programming. Department of Mathematical Sciences, Johns Hopkins University, October, 1992.

• Interior point algorithms for linear programming, Mathematics and Statistics Colloquium, American University, March 26, 1991.

• Convergence of primal-dual interior-point algorithms for linear programming, Numerical Analysis Seminar, Department of Mathematics, University of Maryland College Park, Dec. 6, 1990.