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CORR
2008
Springer
104views Education» more  CORR 2008»
15 years 2 months ago
The Case for Structured Random Codes in Network Capacity Theorems
Random coding arguments are the backbone of most channel capacity achievability proofs. In this paper, we show that in their standard form, such arguments are insufficient for pro...
Bobak Nazer, Michael Gastpar
UAI
1996
15 years 3 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
IJAR
2008
119views more  IJAR 2008»
15 years 2 months ago
Adapting Bayes network structures to non-stationary domains
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
Søren Holbech Nielsen, Thomas D. Nielsen
115
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IJCNLP
2005
Springer
15 years 8 months ago
Using the Structure of a Conceptual Network in Computing Semantic Relatedness
Abstract. We present a new method for computing semantic relatedness of concepts. The method relies solely on the structure of a conceptual network and eliminates the need for perf...
Iryna Gurevych
IJON
2008
109views more  IJON 2008»
15 years 2 months ago
Unsupervised learning neural network with convex constraint: Structure and algorithm
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
Hengqing Tong, Tianzhen Liu, Qiaoling Tong