Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
We consider an opportunistic spectrum access (OSA) problem where the time-varying condition of each channel (e.g., as a result of random fading or certain primary users' activ...
This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
This paper proposes a novel approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large number of object catego...
Database selection is an important step when searching over large numbers of distributed text databases. The database selection task relies on statistical summaries of the databas...