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» Approximation algorithms for budgeted learning problems
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ICASSP
2009
IEEE
15 years 4 months ago
Maximizing global entropy reduction for active learning in speech recognition
We propose a new active learning algorithm to address the problem of selecting a limited subset of utterances for transcribing from a large amount of unlabeled utterances so that ...
Balakrishnan Varadarajan, Dong Yu, Li Deng, Alex A...
TFS
2008
94views more  TFS 2008»
14 years 9 months ago
Hierarchical Fuzzy CMAC for Nonlinear Systems Modeling
Abstract--Since the fuzzy cerebellar model articulation controller (FCMAC) uses linguistic variables, it is highly intuitive and easily comprehended. Despite the FCMAC's good ...
Wen Yu, Floriberto Ortiz Rodriguez, Marco A. Moren...
ICML
2010
IEEE
14 years 10 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
NIPS
2008
14 years 11 months ago
Online Metric Learning and Fast Similarity Search
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kr...
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
15 years 1 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi