**On the ``rough use'' of machine learning techniques**. Keynote at SIGIR, July 25, 2023**Development of open-source machine learning packages**. Talk at MBZUAI, April 4, 2023**Algorithms and software for text classification**. Virtual talk at Bloomberg, November 14, 2022**Optimization and machine learning**. Plenary talk at TWSIAM annual meeting, July 24, 2020**Newton method for convolutional neural networks**. Talk at UCLA Statistics department, November 12, 2019**Lessons learned from developing machine learning algorithms and systems**. Kenote at Technologies and Applications of Artificial Intelligence (TAAI 2017), December 2017. An earlier version was given as an invited talk at Nanyang Technological University, Singapore, January 2017**Large-scale Linear Classification: Status and Challenges**. Invited talk at Criteo Machine Learning workshop, Paris, November, 2017**Optimization and machine learning**. Invited talk at Summer School on Optimization, Big Data and Applications, Italy, July, 2017**Matrix factorization and factorization machines for recommender systems**. Keynote at at 4th Workshop on Large-Scale Recommender Systems, ACM RecSys, September 2016**When and when not to use distributed machine learning**. Keynote at International Winter School on Big Data, Bilbao, Spain, February 2016**Large-scale linear classification**. Course at International Winter School on Big Data, February 2016**Matrix factorization and factorization machines for recommender systems**. Talk at Facebook, November 13, 2015.**Large-scale Linear and Kernel Classification**. Invited talk at Microsoft Research India Machine Learning Summer School, June 15, 2015.**Matrix factorization and factorization machines for recommender systems**. Invited talk at SDM workshop on Machine Learning Methods on Recommender Systems, May 2, 2015.**Large-scale Linear Classification: Status and Challenges**. Talk at San Francisco Machine Learning Meetup, October 30, 2014 (video)**Big-data analytics: challenges and opportunities**. Keynote speech at Taiwan Data Science Conference, Taipei, August 30, 2014.**Large-scale Linear Classification**. Talk at Criteo, August 1, 2014.**Distributed data classification**. Invited talk at Workshop on New Learning Frameworks and Models for Big Data, ICML, June 25, 2014. (also invited talk at Workshop on Scalable Data Analytics, PAKDD, May 13, 2014.)**Recent advances in large linear classification**. Invited talk at Asian Conference on Machine Learning (ACML), November 14, 2013**Experiences and Lessons in Developing Machine Learning and Data Mining Software**. Invited talk at Chinese R Conference, November 2, 2013.**Optimization Methods for Large-scale Linear Classification**. Talk at University of Rome "La Sapienza," June 24, 2013.**Optimization and Machine Learning**. 25th Simon Stevin Lecture, K. U. Leuven Optimization in Engineering Center, January 17, 2013**Large-scale machine learning in distributed environments**. Tutorial talk at K. U. Leuven Optimization in Engineering Center, January 16, 2013.**Support vector machines and kernel methods: status and challenges**. Tutorial talk at K. U. Leuven Optimization in Engineering Center, January 15, 2013.**Machine learning software: design and practical use**. Invited talk at Machine learning summer school (MLSS), Kyoto, 2012. A shorter version was given at another MLSS, Santa Cruz, 2012.**Experiences and lessons in developing industry-strength machine learning and data mining software**. Invited talk at Industry Practice Expo of ACM KDD 2012, Beijing, August 2012.**Large-scale machine learning in distributed environments**. Tutorial talk at ICMR 2012, Hong Kong, June 5, 2012**Recent advances in large linear classification**. Talk at NEC Labs. Cupertino, August 27, 2011.**Support Vector Machines and Kernel Methods**. Plenary talk at International Workshop on Recent Trends in Learning, Computation, and Finance, Pohang, Korea, August 30, 2010.**Feature Engineering and Classifier Ensemble for KDD Cup 2010**Talk at KDD cup workshop, July 25, 2010. This talk explains our approach for winning KDD cup 2010. A more complete version is here**Training support vector machines: status and challenges**Talk at Microsoft Research Asia, October 13, 2009**Training large-scale linear classifiers**Talk at Hong Kong Univ. of Science and Technology, February 5, 2009**Training support vector machines: status and challenges**Invited talk at ICML 2008 Workshop on Large Scale Learning Challenge.**Support vector machines: status and challenges**Talk at Caltech, November 14, 2006**Support vector machines**Tutorial talk at Machine learning summer school, Taipei, 2006. Slides of this talk may be outdated. Please check a more recent talk instead.**Ranking Individuals by Group Comparisons**Talk at International Conference on Machine Learning, June 2006.**Working Set Selection Using Second Order Information for Training SVM**Talk at Workshop on Large Scale Kernel Machines, NIPS 2005.**Optimization, Support Vector Machines, and Machine Learning.**Talk in DIS, University of Rome and IASI, CNR, Italy. September 1-2, 2005. This is a short course introducing optimization researchers about SVM research.**Support vector machines for data classification.**Talk in CWI (Dutch National Research Institute for Mathematics and Computer Science). February 9, 2004.**Some thoughts on machine learning software design.**Talk in University of Southampton, Februaryd 6, 2004.**A practical guide to support vector classification**Talk in University of Freiburg, July 15, 2003.**Can support vector machines become a major classification method ?**Talk in Max Planck Institute, January 29, 2003. PDF file**Support Vector Machines for Data Classification and Regression**Talk in Merck Research Lab., August 16, 2002.**EUNITE Competition: Electricity Load Forecasting**Talk in EUNITE 2001 (winner of EUNITE competition), December 14, 2001.**Support Vector Machines for Data Classification and Regression**Talk in Ford Scientific Research Lab., July 24, 2001. (a similar talk was given at Agilent Inc., July 31, 2001)**IJCNN 2001 Challenge: Generalization Ability and Text Decoding**Talk in IJCNN (winner of IJCNN Challenge), July 17 2001.**Implementation of support vector machines software: theory and practice**Talk in Department of Electrical Engineering, Ohio State University, August 29, 2000.**The analysis of decomposition methods for support vector machines.**Talk in IJCAI 99, Support vector machine workshop. Stockholm, Aug 2, 1999.**Solving Structural Optimization Problems via Semidefinite Programming.**Talk in INFORMS annual meeting, Seattle, October 25-28, 1998.**Preconditioning dense linear systems from large-scale semidefinite programming problems.**Talk in Fifth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado, April, 1998.**Incomplete Cholesky factorizations with limited memory.**Talk in Fourth Kalamazoo Symposium on Matrix Analysis & Applications, Kalamazoo, MI, Oct. 24-25, 1997**Newton's method for large bound-constrained optimization problems.**Talk in International Symposium of Mathematical Programming, Lausanne, Switzerland, August 24-29, 1997.