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NIPS
1997
13 years 8 months ago
Nonlinear Markov Networks for Continuous Variables
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Reimar Hofmann, Volker Tresp
EWCBR
2004
Springer
14 years 24 days ago
Feature Selection and Generalisation for Retrieval of Textual Cases
Textual CBR systems solve problems by reusing experiences that are in textual form. Knowledge-rich comparison of textual cases remains an important challenge for these systems. How...
Nirmalie Wiratunga, Ivan Koychev, Stewart Massie
BIBE
2005
IEEE
13 years 9 months ago
A Multi-Level Approach to SCOP Fold Recognition
The classification of proteins based on their structure can play an important role in the deduction or discovery of protein function. However, the relatively low number of solved...
Keith Marsolo, Srinivasan Parthasarathy, Chris H. ...
JMLR
2010
186views more  JMLR 2010»
13 years 2 months ago
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
Philippos Mordohai, Gérard G. Medioni
IMC
2007
ACM
13 years 9 months ago
Learning network structure from passive measurements
The ability to discover network organization, whether in the form of explicit topology reconstruction or as embeddings that approximate topological distance, is a valuable tool. T...
Brian Eriksson, Paul Barford, Robert Nowak, Mark C...