This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
An analog system-on-chip for kernel-based pattern classification and sequence estimation is presented. State transition probabilities conditioned on input data are generated by an...
Abstract. We present the OnlineDoubleMaxMinOver approach to obtain the Support Vectors in two class classification problems. With its linear time complexity and linear convergence ...
By providing credit risk information, credit rating systems benefit most participants in financial markets, including issuers, investors, market regulators and intermediaries. In ...
A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which thus producing a very difficult...