7378 search results - page 1073 / 1476 » Introduction to Machine Learning |
172
click to vote
JMLR
2002
15 years 6 months ago
2002
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
123
click to vote
ML
2002
ACM
15 years 6 months ago
2002
ACM
When simple parametric models such as linear regression fail to adequately approximate a relationship across an entire set of data, an alternative may be to consider a partition o...
191
click to vote
ML
2002
ACM
15 years 6 months ago
2002
ACM
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
181
Voted
ML
2002
ACM
15 years 6 months ago
2002
ACM
We consider the existence of a linear weak learner for boosting algorithms. A weak learner for binary classification problems is required to achieve a weighted empirical error on t...
198
click to vote
ML
1998
ACM
15 years 6 months ago
1998
ACM
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...