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NIPS
2007
14 years 11 months ago
Predictive Matrix-Variate t Models
It is becoming increasingly important to learn from a partially-observed random matrix and predict its missing elements. We assume that the entire matrix is a single sample drawn ...
Shenghuo Zhu, Kai Yu, Yihong Gong
FLAIRS
2006
14 years 11 months ago
Using Validation Sets to Avoid Overfitting in AdaBoost
AdaBoost is a well known, effective technique for increasing the accuracy of learning algorithms. However, it has the potential to overfit the training set because its objective i...
Tom Bylander, Lisa Tate
LWA
2004
14 years 11 months ago
Modeling Rule Precision
This paper reports first results of an empirical study of the precision of classification rules on an independent test set. We generated a large number of rules using a general co...
Johannes Fürnkranz
NIPS
2004
14 years 11 months ago
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities
We devise and experiment with a dynamical kernel-based system for tracking hand movements from neural activity. The state of the system corresponds to the hand location, velocity,...
Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaa...
NIPS
2004
14 years 11 months ago
Exponential Family Harmoniums with an Application to Information Retrieval
Directed graphical models with one layer of observed random variables and one or more layers of hidden random variables have been the dominant modelling paradigm in many research ...
Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton