Title: An efficient knn-based weighted twin support vector regression
Speaker: Dr. M. Tanveer, IIT Indore
Time: 11:45am, Monday, 23/01/17
Venue: IEOR Teaching Lab, Ground floor, IEOR Bldg
Abstract: In general, pattern classification and regression tasks do not take into consideration the variation in the importance of the training samples. For twin support vector regression (TSVR), this implies that all the training samples play the same role on the bound functions. However, the number of close neighboring samples near to each training sample has an effect on the bound functions. In this talk, we formulate a regularized version of the knn-based weighted twin support vector regression (KNNWTSVR) called RKNNWTSVR which is both efficient and effective. By introducing the regularization term and replacing 2-norm of slack variables instead of 1-norm, our RKNNWTSVR only needs to solve a simple system of linear equations with low computational cost, and at the same time, it improves the generalization performance. Particularly, we compare four implementations of RKNNWTSVR with existing approaches. Experimental results on several synthetic and benchmark datasets indicate that, comparing to SVR, TSVR and KNNWTSVR, our approach has better generalization ability and requires less computational time.
Speaker bio: Dr. M. Tanveer is a Ramanujan Fellow at the Discipline of Mathematics of the Indian Institute of Technology Indore since July, 2016. Prior to that he spent one year as a Postdoctoral Research Fellow at the Rolls-Royce@NTU Corporate Lab of the Nanyang Technological University (NTU) Singapore. He received the PhD degree in Computer Science from Jawaharlal Nehru University (JNU) New Delhi and M.Phil degree in Mathematics from Aligarh Muslim University. His research interests include support vector machines, optimization, applications to Alzheimer�s disease and dementias, biomedical signal processing, and fixed point theory and applications. Dr. Tanveer is the recipient of the 2016 Ramanujan Fellowship (one of the most prestigious awards of INDIA). He is the reviewer of American Mathematical Society, USA, and a member of the editorial review board of Applied Intelligence, Springer (International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies).