Branch predictors typically use combinations of branch PC bits and branch histories to make predictions. Recent improvements in branch predictors have come from reducing the effec...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce an incremental algorithm u...
Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better u...
Bioinformatics aims at applying computer science methods to the wealth of data collected in a variety of experiments in life sciences (e.g. cell and molecular biology, biochemistry...