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ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
TSMC
2008
100views more  TSMC 2008»
13 years 7 months ago
Instruction-Matrix-Based Genetic Programming
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...
NIPS
2004
13 years 9 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
JAIR
2007
113views more  JAIR 2007»
13 years 7 months ago
Chain: A Dynamic Double Auction Framework for Matching Patient Agents
In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a res...
Jonathan Bredin, David C. Parkes, Quang Duong
PAKDD
2001
ACM
157views Data Mining» more  PAKDD 2001»
14 years 3 days ago
Applying Pattern Mining to Web Information Extraction
Information extraction (IE) from semi-structured Web documents is a critical issue for information integration systems on the Internet. Previous work in wrapper induction aim to so...
Chia-Hui Chang, Shao-Chen Lui, Yen-Chin Wu