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» Approximation Methods for Supervised Learning
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ECML
2005
Springer
14 years 2 months ago
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
Masoumeh T. Izadi, Doina Precup
IGARSS
2010
13 years 3 months ago
Calibrating probabilities for hyperspectral classification of rock types
This paper investigates the performance of machine learning methods for classifying rock types from hyperspectral data. The main objective is to test the impact on classification ...
Sildomar T. Monteiro, Richard J. Murphy
CVPR
2011
IEEE
13 years 14 days ago
Compact Hashing with Joint Optimization of Search Accuracy and Time
Similarity search, namely, finding approximate nearest neighborhoods, is the core of many large scale machine learning or vision applications. Recently, many research results dem...
Junfeng He, Regunathan Radhakrishnan, Shih-Fu Chan...
COMCOM
2008
127views more  COMCOM 2008»
13 years 8 months ago
A dynamic routing protocol for keyword search in unstructured peer-to-peer networks
The idea of building query-oriented routing indices has changed the way of improving keyword search efficiency from the basis as it can learn the content distribution from the que...
Cong Shi, Dingyi Han, Yuanjie Liu, Shicong Meng, Y...
CVPR
2008
IEEE
14 years 10 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell