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» On the hyperbolicity constant in graphs
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ILP
2003
Springer
15 years 11 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
ESA
2006
Springer
77views Algorithms» more  ESA 2006»
15 years 9 months ago
Traversing the Machining Graph
Abstract. Zigzag pocket machining (or 2D-milling) plays an important role in the manufacturing industry. The objective is to minimize the number of tool retractions in the zigzag m...
Danny Z. Chen, Rudolf Fleischer, Jian Li, Haitao W...
MST
2011
209views Hardware» more  MST 2011»
15 years 1 months ago
Spreading of Messages in Random Graphs
Chang and Lyuu [Chang and Lyuu, 2008] study the spreading of a message in an Erd˝os-R´enyi random graph G(n, p) starting from a set of vertices that are convinced of the message...
Ching-Lueh Chang, Yuh-Dauh Lyuu
MFCS
2009
Springer
16 years 22 days ago
Balanced Paths in Colored Graphs
We consider finite graphs whose edges are labeled with elements, called colors, taken from a fixed finite alphabet. We study the problem of determining whether there is an infi...
Alessandro Bianco, Marco Faella, Fabio Mogavero, A...
PKDD
2009
Springer
155views Data Mining» more  PKDD 2009»
16 years 22 days ago
Dynamic Factor Graphs for Time Series Modeling
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
Piotr W. Mirowski, Yann LeCun