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» Approximate algorithms for neural-Bayesian approaches
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STOC
1997
ACM
125views Algorithms» more  STOC 1997»
15 years 2 months ago
An Interruptible Algorithm for Perfect Sampling via Markov Chains
For a large class of examples arising in statistical physics known as attractive spin systems (e.g., the Ising model), one seeks to sample from a probability distribution π on an...
James Allen Fill
BMCBI
2010
117views more  BMCBI 2010»
14 years 10 months ago
New decoding algorithms for Hidden Markov Models using distance measures on labellings
Background: Existing hidden Markov model decoding algorithms do not focus on approximately identifying the sequence feature boundaries. Results: We give a set of algorithms to com...
Daniel G. Brown 0001, Jakub Truszkowski
IJCNN
2006
IEEE
15 years 3 months ago
Greedy forward selection algorithms to Sparse Gaussian Process Regression
Abstract— This paper considers the basis vector selection issue invloved in forward selection algorithms to sparse Gaussian Process Regression (GPR). Firstly, we re-examine a pre...
Ping Sun, Xin Yao
KAIS
2008
150views more  KAIS 2008»
14 years 10 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng
FTDB
2011
98views more  FTDB 2011»
14 years 1 months ago
Secure Distributed Data Aggregation
We present a survey of the various families of approaches to secure aggregation in distributed networks such as sensor networks. In our survey, we focus on the important algorithm...
Haowen Chan, Hsu-Chun Hsiao, Adrian Perrig, Dawn S...