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PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
14 years 4 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
ICDM
2007
IEEE
138views Data Mining» more  ICDM 2007»
14 years 4 months ago
Bandit-Based Algorithms for Budgeted Learning
We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is s...
Kun Deng, Chris Bourke, Stephen D. Scott, Julie Su...
ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
14 years 4 months ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti
ICDM
2006
IEEE
127views Data Mining» more  ICDM 2006»
14 years 4 months ago
Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions
There is a need to develop methods to automatically incorporate prior knowledge to support the prediction and validation of novel functional associations. One such important sourc...
Francisco Azuaje, Haiying Wang, Huiru Zheng, Olivi...
ICDM
2003
IEEE
143views Data Mining» more  ICDM 2003»
14 years 3 months ago
Active Sampling for Feature Selection
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Sriharsha Veeramachaneni, Paolo Avesani