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» On learning algorithm selection for classification
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ICML
2006
IEEE
16 years 7 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ECIR
2010
Springer
15 years 8 months ago
Query Difficulty Prediction for Contextual Image Retrieval
Abstract. This paper explores how to predict query difficulty for contextual image retrieval. We reformulate the problem as the task of predicting how difficult to represent a quer...
Xing Xing, Yi Zhang 0001, Mei Han
ICML
2010
IEEE
15 years 7 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
DIS
2004
Springer
15 years 10 months ago
Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data
Abstract. Attribute value taxonomies (AVTs) have been used to perform AVT-guided decision tree learning on partially or totally missing data. In many cases, user-supplied AVTs are ...
Jinu Joo, Jun Zhang 0002, Jihoon Yang, Vasant Hona...
ICML
1998
IEEE
16 years 7 months ago
Learning Collaborative Information Filters
Predicting items a user would like on the basis of other users' ratings for these items has become a well-established strategy adopted by many recommendation services on the ...
Daniel Billsus, Michael J. Pazzani