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IJCNN
2000
IEEE
14 years 2 days ago
On MCMC Sampling in Bayesian MLP Neural Networks
Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Aki Vehtari, Simo Särkkä, Jouko Lampinen
CVIU
2006
176views more  CVIU 2006»
13 years 7 months ago
Temporal motion models for monocular and multiview 3D human body tracking
We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...
Raquel Urtasun, David J. Fleet, Pascal Fua
CP
2010
Springer
13 years 6 months ago
Computing the Density of States of Boolean Formulas
Abstract. In this paper we consider the problem of computing the density of states of a Boolean formula in CNF, a generalization of both MAX-SAT and model counting. Given a Boolean...
Stefano Ermon, Carla P. Gomes, Bart Selman
ICML
2000
IEEE
14 years 8 months ago
Eligibility Traces for Off-Policy Policy Evaluation
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh
SEMWEB
2005
Springer
14 years 1 months ago
Modeling the Non-Expected Choice: A Weighted Utility Logit
This work derives and simulates two choice models applying the weighted utility theory, a generalization of the expected utility theory. It shows one set of assumptions, which jus...
Pia Koskenoja