This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program perform...
Kapil Vaswani, Matthew J. Thazhuthaveetil, Y. N. S...
In this paper, Multi-View Expectation and Maximization algorithm for finite mixture models is proposed by us to handle realworld learning problems which have natural feature split...
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements t...
Lorenzo Carlucci, Sanjay Jain, Efim B. Kinber, Fra...
An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perfor...