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IJCAI
2007
13 years 10 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell
NIPS
2008
13 years 10 months ago
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
Indraneel Mukherjee, David M. Blei
SCAI
2008
13 years 10 months ago
Modeling Habituation in the Cnidarian Hydra
Abstract. In the design of behavior-based control architectures for robots it is common to use biology as inspiration, and often the observed functionalities of insect behaviors ar...
Malin Aktius, Mats Nordahl, Tom Ziemke
SDM
2008
SIAM
140views Data Mining» more  SDM 2008»
13 years 10 months ago
Large-Scale Many-Class Learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Michael Connor
SODA
2008
ACM
101views Algorithms» more  SODA 2008»
13 years 10 months ago
Adaptive local ratio
Local ratio is a well-known paradigm for designing approximation algorithms for combinatorial optimization problems. At a very high level, a local-ratio algorithm first decomposes ...
Julián Mestre