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ICML
2007
IEEE
14 years 9 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
ICDE
2008
IEEE
158views Database» more  ICDE 2008»
14 years 10 months ago
CARE: Finding Local Linear Correlations in High Dimensional Data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
Xiang Zhang, Feng Pan, Wei Wang
UAI
2000
13 years 10 months ago
Learning to Cooperate via Policy Search
Cooperative games are those in which both agents share the same payoff structure. Valuebased reinforcement-learning algorithms, such as variants of Q-learning, have been applied t...
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Les...
CVPR
2005
IEEE
14 years 10 months ago
Boosting Saliency in Color Image Features
The aim of salient point detection is to find distinctive events in images. Salient features are generally determined from the local differential structure of images. They focus o...
Joost van de Weijer, Theo Gevers
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
14 years 2 months ago
A graph-theoretic approach to extract storylines from search results
We present a graph-theoretic approach to discover storylines from search results. Storylines are windows that offer glimpses into interesting themes latent among the top search re...
Ravi Kumar, Uma Mahadevan, D. Sivakumar