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ALT
2006
Springer
15 years 6 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
AAAI
2010
14 years 11 months ago
Gaussian Mixture Model with Local Consistency
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
Jialu Liu, Deng Cai, Xiaofei He
88
Voted
CP
2009
Springer
15 years 4 months ago
Reasoning about Optimal Collections of Solutions
The problem of finding a collection of solutions to a combinatorial problem that is optimal in terms of an inter-solution objective function exists in many application settings. F...
Tarik Hadzic, Alan Holland, Barry O'Sullivan
NIPS
1990
14 years 10 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
PAMI
2008
135views more  PAMI 2008»
14 years 9 months ago
MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm
In this paper, we develop a new effective multiple kernel learning algorithm. First, we map the input data into m different feature spaces by m empirical kernels, where each genera...
Zhe Wang, Songcan Chen, Tingkai Sun