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» Input and Structure Selection for k-NN Approximator
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UAI
2003
13 years 7 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
AIPS
2007
13 years 8 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
BMCBI
2010
175views more  BMCBI 2010»
13 years 5 months ago
Calibur: a tool for clustering large numbers of protein decoys
Background: Ab initio protein structure prediction methods generate numerous structural candidates, which are referred to as decoys. The decoy with the most number of neighbors of...
Shuai Cheng Li, Yen Kaow Ng
ICCAD
2003
IEEE
123views Hardware» more  ICCAD 2003»
14 years 2 months ago
A Hybrid Approach to Nonlinear Macromodel Generation for Time-Varying Analog Circuits
Modeling frequency-dependent nonlinear characteristics of complex analog blocks and subsystems is critical for enabling efficient verification of mixed-signal system designs. Rece...
Peng Li, Xin Li, Yang Xu, Lawrence T. Pileggi
IJCNN
2007
IEEE
14 years 2 days ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot