This paper explores the use of Bayesian online classifiers to classify text documents. Empirical results indicate that these classifiers are comparable with the best text classifi...
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...