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» Learning Weighted Automata
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CSB
2004
IEEE
149views Bioinformatics» more  CSB 2004»
14 years 1 months ago
Weighting Features to Recognize 3D Patterns of Electron Density in X-Ray Protein Crystallography
Feature selection and weighting are central problems in pattern recognition and instance-based learning. In this work, we discuss the challenges of constructing and weighting feat...
Kreshna Gopal, Tod D. Romo, James C. Sacchettini, ...
ACML
2009
Springer
14 years 4 months ago
Community Detection on Weighted Networks: A Variational Bayesian Method
Abstract. Massive real-world data are network-structured, such as social network, relationship between proteins and power grid. Discovering the latent communities is a useful way f...
Qixia Jiang, Yan Zhang, Maosong Sun
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
14 years 3 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
ECML
2007
Springer
14 years 4 months ago
Class Noise Mitigation Through Instance Weighting
We describe a novel framework for class noise mitigation that assigns a vector of class membership probabilities to each training instance, and uses the confidence on the current ...
Umaa Rebbapragada, Carla E. Brodley
ECML
2007
Springer
14 years 4 months ago
Nondeterministic Discretization of Weights Improves Accuracy of Neural Networks
Abstract. The paper investigates modification of backpropagation algorithm, consisting of discretization of neural network weights after each training cycle. This modification, a...
Marcin Wojnarski