We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...