Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection met...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Extracting key-frames is the first step for efficient content-based indexing, browsing and retrieval of the video data in commercial movies. Most of the existing research deals wi...
Whether common ancestors of eukaryotes and prokaryotes had introns is one of the oldest unanswered questions in molecular evolution. Recently completed genome sequences have been u...
-- Publishing person specific data while protecting privacy is an important problem. Existing algorithms that enforce the privacy principle called l-diversity are heuristic based d...