Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
We make two main contributions in this paper. First, we motivate and introduce a novel class of data mining problems that arise in labeling a group of mass spectra, specifically f...
In this paper, we consider the problem of categorizing
videos of dynamic textures under varying view-point. We
propose to model each video with a collection of Linear
Dynamics S...
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
Abstract. We address the revision problem for knowledge bases (KBs) in Description Logics (DLs). This problem has received much attention in the ontology management and DL communit...