MIWAI'2014

MIWAI 2014 Tutorial/Workshop Schedule download here.

Multi-disciplinary International Workshop on Artificial Intelligence(MIWAI-2014) (8th December to 10th December 2014) Venue: Senate Hall, Capitol Hotel, Bangalore, India
8th December 2014
8:30 A.M to 9:30 A.M:	Registration
9:30 A.M to 11:00 A.M:	Tutorial-1 [Part I] Speaker: Dr. Chattrakul Sombattheera, Mahasarakham University, Thailand Title: Introduction to Coalition Formation Chair: TBD
11:00 A.M to 11:30 A.M:	Tea Break
11:30 A.M to 01:00 0P.M:	Tutorial-1 [Part II] Speaker: Dr. Chattrakul Sombattheera, Mahasarakham University, Thailand Title: Introduction to Coalition Formation Chair: TBD
1:00P.M to 2:00 P.M:	Lunch Break
2:00 P.M to 03:30 P.M:	Tutorial-2 [Part I] Speaker: Prof. P. Krishna Reddy, IIIT Hyderabad Title: "Building of eSagu System", an IT-based Personalized Agro-Advisory system. Chair: TBD
03:30 P.M to 04:00 P.M:	Tea Break
04:00 P.M to 05:30 P.M:	Tutorial-2 [Part II] Speaker: Prof. P. Krishna Reddy, IIIT Hyderabad Title: "Building of eSagu System", an IT-based Personalized Agro-Advisory system. Chair: TBD
9th December 2014
8:00 A.M to 9:30 A.M:	Registration
9:30 A.M to 10 A.M:	Inauguration ceremony
10:00 A.M to 11:00 A.M:	Keynote Talk: Prof. C. A. Murthy, ISI Kolkata Title: Face Recognition using Set Estimation Procedure Chair: Prof. Y. Narahari, IISc Bangalore
11:00 A.M to 11:30 A.M:	Tea Break
11:30 A.M to 1:00 P.M:	Technical Session-1: Evolutionary Computing and Others-I Session Chair: TBD "Potential Interval of root" of Nonlinear Equation: Labeling Algorithm; Vijaya Lakshmi V. Nadimpalli, Rajeev Wankar and Raghavendra Rao Chillarige Stochastic Leaky Integrator Model for Interval Timing; Komala Anamalamudi, Bapi Raju Surampudi and Madhavilatha Maganti Multi-Objective Exploration for Compiler Optimizations & Parameters; N A B Sankar Chebolu and Rajeev Wankar
1:00P.M to 2:00 P.M:	Lunch Break
2:00 P.M to 3:00 P.M:	Invited Talk-1: Prof. P. S. Sastry, IISc Bangalore Title: Learning classifiers under label noise Chair: TBD
3:00 P.M to 4:00 P.M:	Technical Session-2: Evolutionary Computing and Others-II Session Chair: TBD Association Rule Mining via Evolutionary Multi-objective Optimization; Ganghishetti Pradeep and Ravi Vadlamani DC charger selection scheme for electric vehicles based on a distance-based heuristic; Junghoon Lee Automated Reasoning in Deontic Logic; Claudia Schon, Ulrich Furbach and Frieder Stolzenburg
4:00 P.M to 4:30 P.M	Tea Break
4:30 P.M to 5:30 P.M:	Technical Session-3: Soft Computing –I Session Chair: TBD Image Processing Tool for FAE Cloud Dynamics; Mousumi Roy, Allam Apparao, Arun Agarwal, Rajeev Wankar and Raghavendra Rao Chillarige N-gram Based Approach for Opinion Mining of Punjabi Text; Amandeep Kaur and Vishal Gupta Application of Game-theoretic Rough Sets in Recommender Systems; Nouman Azam and Jingtao Yao
7:00 P.M to 10:00 P.M:	Cultural Programme and Workshop Banquet Dinner Venue: The Capitol Hotel
10th December 2014
9:00 A.M to 10:00 A.M:	Invited Talk-2: Prof. B. S. Daya Sagar, ISI, Bangalore Title: Greyscale Morphological Interpolations and Morphing Chair: TBD
10:00 A.M to 11:00 A.M:	Technical Session-4: Soft-Computing-II Session Chair: TBD RGB - based Color Texture Image Classification using Anisotropic Diffusion and LDBP; Prakash Hiremath and Rohini Bhusnurmath A Knowledge-based Design for Structural Analysis of Printed Mathematical Expressions; Pavan Kumar P, Arun Agarwal and Chakravarthy Bhagvati A New Preprocessor to Fuzzy c-Means Algorithm; Raveen S, Sai Prasad P.S.V.S and Raghavendra Rao Chillarige
11:00 A.M to 11:30 A.M:	Tea Break
11:30 A.M to 1:00 P.M:	Technical Session-5: DM/ML Session Chair: TBD Domain Specific Sentiment Dictionary for Opinion Mining of Vietnamese Text; Hong Nam Nguyen, Van Le Thanh, Hai Son Le and Vu Pham Tran Support Vector-Quantile Regression Random Forest hybrid for Regression Problems; Ravi Vadlamani and Anurag Sharma Clustering Web Services on Frequent Output Parameters for I/O based Service Search; Lakshmi H N and Hrushikesha Mohanty IntelliNavi : Navigation for Blind based on Kinect and Machine Learning; Alexy Bhowmick, Saurabh Prakash, Rukmani Bhagat, Vijay Prasad and Shyamanta M. Hazarika
1:00 P.M to 2:00 P.M:	Lunch Break
2:00 PM to 3:00 PM:	Invited Talk-3: Dr. Biplav Srivastava, IBM Research, New Delhi Title: Open Innovation - From Government Open Data to Societal Applications that Matter Chair: TBD
3:00 P.M to 4:40 P.M:	Technical Session-6: Web/NW Session Chair: TBD A trust metric for online virtual teams & work groups; Sagar A B and Hrushikesha Mohanty Web Service Composition Using Service Maps; Supriya Vaddi and Hrushikesha Mohanty Integrated Representation of Spatial Topological and Size Relations for the Semantic Web; Sotiris Batsakis, Grigoris Antoniou and Ilias Tachmazidis Using Bayesian Networks to Model and Analysis Software Product Line Feature Model; Musfiqur Rahman and Shamim Ripon A content-based approach for user profile modeling and matching on social network; Van Le Thanh, Nghia Truong Trong and Vu Pham Tran
4:40 P.M to 5:00 P.M:	Tea Break
5:00 P.M to 5:30 P.M:	Valedictory

[View all speakers details]

Prof. C. A. Murthy (Keynote Speaker)

Prof. C. A. Murthy Machine Intelligence Unitarianize Indian Statistical Institute 203 Barrackpore Trunk Road Kolkata - 700 108 India Email: murthy@isical.ac.in http://www.isical.ac.in/~murthy/ More...

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Prof. P. S. Sastry (Invited Speaker)

Prof. P. S. Sastry Room No 235 Department of Electrical Engineering Indian Institute of Science Bangalore-560012 India Email: sastry@ee.iisc.ernet.in http://minchu.ee.iisc.ernet.in/new/people/faculty/pss/ More...

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Brief Biography: Professor P.S Sastry received B.Sc.(Hons.) in Physics from IIT, Kharagpur, in 1978 and B.E. in Electrical Communications Engineering and Ph.D. from Department of Electrical Engineering, from IISc, Bangalore in 1981 and 1985 respectively. Since 1986, he has been a faculty member in the department of Electrical Engineering, Indian Institute of Science, Bangalore, where currently he is a professor. He has held visiting positions at University of Massachusetts, Amherst, University of Michigan, Ann Arbor and General Motors Research Labs, Warren, USA. He is an Associate Editor of IEEE Transactions on Systems, Man and Cybernetics since 2001 and IEEE Transactions on Automation Science and Engineering (2007-10). He is a recipient of Sir C.V.Raman Young Scientist award, from Govt of Karnataka, Hari Om Ashram Dr. Vikram Sarabhai research award from PRL and Most Valued Colleague award from General Motors Corporation. He is a Fellow of Indian National Academy of Engineering and a Senior Member of IEEE. He has around 45 high quality publications. He also has 3 patents to his credit. His research interests include Machine Learning, Pattern Recognition, Data Mining and Computational Neuroscience.

Title: Learning classifiers under label noise

Abstract: Supervised learning of pattern classifiers is a basic problem in Machine Learning. One uses a training set of patterns vectors with known class labels for learning the classifier. In many applications the labels provided for the training patterns may be incorrect and this is termed as label noise. This problem is important in many applications today where the labels may have been obtained through, e.g., crowd sourcing. Obviously it is desirable to have learning algorithms that can learn good classifiers even though the training set may be corrupted with label noise. Many approaches have been proposed for identifying and/or guarding against training examples with noisy labels. In the first part of this talk we will review some of the approaches based on heuristics and also some of the recent approaches that are based on some interesting statistical principles. In the second part of the talk we concentrate of one generic approach to classifier learning, namely, risk minimization. We present some of our recent results on making risk minimization robust to label noise. We consider the cases of both uniform and non-uniform label noise. In the uniform noise case, the probability of class label being incorrect is same for all feature vectors while under the non-uniform label noise, the probability of the class label being incorrect can be a function of the feature vector. We present some sufficient conditions on the loss function that would make risk minimization robust to label noise. While none of the popular convex loss functions such as the hinge loss (which is used in SVM), the exponential loss (which is used in AdaBoost) etc. satisfy the sufficient conditions, we show that ramp loss, sigmoid loss and the 0-1 loss satisfy the sufficient condition. We also discuss some algorithmic issues in minimizing empirical risk under the noise-robust loss functions. We present some empirical results that demonstrate the relevance of these theoretical results.

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Dr. B. S. Daya Sagar (Invited Speaker)

Dr. B. S. Daya Sagar Associate Professor & Head Systems Science and Informatics Unit (SSIU) Indian Statistical Institute--Bangalore Centre 8th Mile, Mysore Road, R. V. College P.O Bangalore-560059 India Email: bsdsagar@isibang.ac.in http://www.isibang.ac.in/~bsdsagar/ More...

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Dr. Biplav Srivastava (Invited Speaker)

Dr. Biplav Srivastava Senior Researcher, IBM Master Inventor IBM Research, ISID Campus, Plot No. 4, Block C, Institutional Area, Vasant Kunj New Delhi - 110 070 India Email: sbiplav@in.ibm.com http://www.research.ibm.com/people/b/biplav/ More...

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Dr. P. Krishna Reddy (Tutorial Speaker)

Dr P.Krishna Reddy Program Director, ITRA Agriculture & Food, DietY, Govt. of India and Professor International Institute of Information Technology Hyderabad (IIIT-H) Gachibowli, Hyderabad, Telangana State 500032 India E-mail: pkreddy@iiit.ac.in http://www.iiit.ac.in/~pkreddy/ More...

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Dr. Chattrakul Sombattheera (Tutorial Speaker)

Dr. Chattrakul Sombattheera Faculty of Informatics Mahasarakham University Khamreang Sub-District Kantarawichai District Maha Sarakham 44150 Thailand Email: chattrakul.s@msu.ac.th More...