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» Evaluating algorithms that learn from data streams
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ICMCS
2006
IEEE
125views Multimedia» more  ICMCS 2006»
16 years 16 days ago
Usability Evaluation for Image Retrieval Beyond Desktop Applications
Interactivity is a key concept in modern content-based retrieval. Therefore, in addition to the ability to learn from user generated data, easy and intuitive to use interfaces are...
Thomas Käster, Michael Pfeiffer, Christian Ba...
LWA
2007
15 years 8 months ago
Meta-Learning Rule Learning Heuristics
The goal of this paper is to investigate to what extent a rule learning heuristic can be learned from experience. Our basic approach is to learn a large number of rules and record ...
Frederik Janssen, Johannes Fürnkranz
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
16 years 7 months ago
Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
Edoardo Airoldi, Xue Bai, Rema Padman
NIPS
2000
15 years 7 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
ICASSP
2011
IEEE
14 years 10 months ago
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization
In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
Xueru Zhang, Kris Demuynck, Hugo Van hamme