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PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
13 years 6 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
PVLDB
2010
132views more  PVLDB 2010»
13 years 6 months ago
CoDA: Interactive Cluster Based Concept Discovery
Large data resources are ubiquitous in science and business. For these domains, an intuitive view on the data is essential to fully exploit the hidden knowledge. Often, these data...
Stephan Günnemann, Ines Färber, Hardy Kr...
PVLDB
2010
112views more  PVLDB 2010»
13 years 6 months ago
On Triangulation-based Dense Neighborhood Graphs Discovery
This paper introduces a new definition of dense subgraph pattern, the DN-graph. DN-graph considers both the size of the sub-structure and the minimum level of interactions betwee...
Nan Wang, Jingbo Zhang, Kian-Lee Tan, Anthony K. H...
ICDM
2010
IEEE
216views Data Mining» more  ICDM 2010»
13 years 6 months ago
K-AP: Generating Specified K Clusters by Efficient Affinity Propagation
Abstract--The Affinity Propagation (AP) clustering algorithm proposed by Frey and Dueck (2007) provides an understandable, nearly optimal summary of a data set. However, it suffers...
Xiangliang Zhang, Wei Wang, Kjetil Nørv&ari...
ICDM
2010
IEEE
167views Data Mining» more  ICDM 2010»
13 years 6 months ago
Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori...