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ICML
2000
IEEE
16 years 15 days ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
ICML
2010
IEEE
15 years 23 days ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
CVPR
2010
IEEE
15 years 8 months ago
Online-Batch Strongly Convex Multi Kernel Learning
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
Francesco Orabona, Jie Luo, Barbara Caputo
UAI
2003
15 years 1 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
CIKM
2009
Springer
15 years 6 months ago
Learning to rank graphs for online similar graph search
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
Bingjun Sun, Prasenjit Mitra, C. Lee Giles