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» Predictive Matrix-Variate t Models
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PPOPP
2006
ACM
16 years 1 months ago
Minimizing execution time in MPI programs on an energy-constrained, power-scalable cluster
Recently, the high-performance computing community has realized that power is a performance-limiting factor. One reason for this is that supercomputing centers have limited power ...
Robert Springer, David K. Lowenthal, Barry Rountre...
ICANN
2009
Springer
15 years 11 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
ESEM
2008
ACM
15 years 8 months ago
Iterative identification of fault-prone binaries using in-process metrics
Code churn, the amount of code change taking place within a software unit over time, has been correlated with fault-proneness in software systems. We investigate the use of code c...
Lucas Layman, Gunnar Kudrjavets, Nachiappan Nagapp...
SDM
2010
SIAM
149views Data Mining» more  SDM 2010»
15 years 8 months ago
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization
Real-world relational data are seldom stationary, yet traditional collaborative filtering algorithms generally rely on this assumption. Motivated by our sales prediction problem, ...
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff Schneide...
IJCAI
1997
15 years 8 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida