The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...
In the automatic design of custom instruction set processors, there can be a very large set of potential custom instructions, from which a few instructions are required to be chos...