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AAAI
2010
13 years 9 months ago
To Max or Not to Max: Online Learning for Speeding Up Optimal Planning
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...
Carmel Domshlak, Erez Karpas, Shaul Markovitch
IPMI
2009
Springer
14 years 8 months ago
Estimating Uncertainty in Brain Region Delineations
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
ICML
2006
IEEE
14 years 8 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
VLSISP
1998
111views more  VLSISP 1998»
13 years 7 months ago
Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
Yue Wang, Tülay Adali, Chi-Ming Lau, Sun-Yuan...
CSDA
2006
98views more  CSDA 2006»
13 years 8 months ago
GS-distributions: A new family of distributions for continuous unimodal variables
The choice of the best-suited statistical distribution for modeling data is not a trivial issue. Unless a sound theoretical background exists for selecting a particular distributi...
J. M. Muiño, Eberhard O. Voit, Albert Sorri...