The International School of Information Management (ISiM), University of Mysore is organizing a Workshop on Machine Learning - its second Executive Education Programme during April 21-25 in Bangalore. (www.isim.ac.in/mlw) The Workshop faculty is Prof. Sargur Srihari, SUNY Distinguished Professor of Computer Science and Engineering at the University at Buffalo, State University of New York, USA and Visiting Faculty at ISiM. Professor Srihari, author of more than 300 research papers including 6 US patents, is the founding director of CEDAR (Centre of Excellence for Document Analysis and Recognition) and a well-known expert in pattern recognition and Machine Learning. Registration fee: Rs. 15000/-* per participant (Earn yourself 3 credits from this Executive Education Programme) Limited seats available. Registration on first come, first serve basis. Focus of the Workshop: Balancing theory and practice, this Workshop, will focus on the following applications: · Information Retrieval, · Language Processing, · Document Analysis · Speech Recognition Objectives of the workshop: · Introduce participants to concepts of ML including concepts of clustering, Gaussian mixtures and dimensionality reduction · Enable the use of the state of the art methods and tools in ML techniques · Provide an overview of the major areas of applications of ML · An in depth understanding of ML applications in the four focus areas - Information Retrieval; Language Processing; Document Analysis and Speech Recognition · Provide hands on training on the key techniques Course Outline Module 1. Introduction: What is ML; Discriminative vs Generative ; Regression Example Module 2: Probability Theory ; Decision Theory ; Information Theory ; Probability Distributions ; Linear Regression Models ; Linear Basis Functions ; Bias-Variance Trade-off ; Bayesian Linear Regression Module 3. Neural Networks and Kernel Machines: Biological Motivation; Perceptrons ; Multilayer Networks and Backpropagation ; Representational Power; Applications ; Support Vector Machines Module 4. Graphical Models and EM: Bayesian Networks; Conditional Independence; Markov Random Fields ; Inference in Graphical Models ; K-means Clustering ; Mixtures of Gaussians Module 5. Sampling Methods: Basic Sampling Methods; Monte Carlo Methods, Gibbs Sampling Module 6: Sequential Data : Markov Models ; Hidden Markov Models ; Extensions to HMMs ; Linear Dynamical Systems ; Conditional Random Fields Module 7. ML Applications with focus on Information Retrieval, Document Analysis and Recognition, Natural Language Processing, Data Mining Participant Profile This Workshop is designed for academicians and professionals in Computer Science and Engineering, Statistics and Social Sciences. The workshop is mainly targeted for: · Academicians and industry practitioners of ML · Professionals working in the areas of Information Retrieval, Language Processing, Document Analysis and Speech Recognition · Researchers working in the application areas but new to ML · Students pursuing projects in ML Workshop Highlights and Benefits to Participants · Get a panoramic view of ML · Understand the basics of ML · Learn the latest tools and techniques used in ML · Get hands on experience on developing basic biometric, character and image recognition modules · Gain knowledge of implementing advanced classifiers and boosting · Get exposure to new arenas of research and projects Workshop Venue Informatics (India) Ltd. No. 194, R.V. Road Basavanagudi, P.B. No. 400 Bangalore 560 004 For more details Please contact Angrosh at 9886970411 or mail to office@isim.ac.in *Registration fee includes workshop material, lunch and refreshments ************************************************ M. A. Angrosh Project Manager International School of Information Management University of Mysore, Manasagangotri Mysore - 570 006 Tel: +91-821-2514699; Fax: +91-821-2519209 Email: angrosh@isim.ac.in Website: www.isim.ac.in ************************************************* -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean.