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88
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MICRO
1999
IEEE
123views Hardware» more  MICRO 1999»
15 years 3 months ago
Improving Branch Predictors by Correlating on Data Values
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...
Timothy H. Heil, Zak Smith, James E. Smith
NIPS
2008
15 years 10 days ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
94
Voted
COLT
2004
Springer
15 years 2 months ago
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions
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...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...
111
Voted
EDM
2009
147views Data Mining» more  EDM 2009»
14 years 8 months ago
Using Dirichlet priors to improve model parameter plausibility
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...
Dovan Rai, Yue Gong, Joseph Beck
113
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CONSTRAINTS
2008
182views more  CONSTRAINTS 2008»
14 years 11 months ago
Constraint Programming in Structural Bioinformatics
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...
Pedro Barahona, Ludwig Krippahl