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» Learning with Weighted Transducers
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ACML
2009
Springer
14 years 3 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 2 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 3 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 3 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
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
14 years 1 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang