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» Approximation Methods for Supervised Learning
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GECCO
2009
Springer
134views Optimization» more  GECCO 2009»
15 years 4 months ago
Estimating the distribution and propagation of genetic programming building blocks through tree compression
Shin et al [19] and McKay et al [15] previously applied tree compression and semantics-based simplification to study the distribution of building blocks in evolving Genetic Progr...
Robert I. McKay, Xuan Hoai Nguyen, James R. Cheney...
ECML
2006
Springer
15 years 3 months ago
Prioritizing Point-Based POMDP Solvers
Recent scaling up of POMDP solvers towards realistic applications is largely due to point-based methods such as PBVI, Perseus, and HSVI, which quickly converge to an approximate so...
Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony
RIAO
2007
15 years 1 months ago
Discriminative Fields for Modeling Semantic Concepts in Video
According to some current thinking, a very large number of semantic concepts could provide researcher a novel way to characterize video and be utilized for video retrieval and und...
Ming-yu Chen, Alexander G. Hauptmann
PAMI
2006
147views more  PAMI 2006»
14 years 11 months ago
Bayesian Gaussian Process Classification with the EM-EP Algorithm
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Hyun-Chul Kim, Zoubin Ghahramani
ICML
2007
IEEE
16 years 17 days ago
Efficient inference with cardinality-based clique potentials
Many collective labeling tasks require inference on graphical models where the clique potentials depend only on the number of nodes that get a particular label. We design efficien...
Rahul Gupta, Ajit A. Diwan, Sunita Sarawagi