JMLR
2012
12 years 1 months ago
2012
We prove logarithmic regret bounds that depend on the loss L∗ T of the competitor rather than on the number T of time steps. In the general online convex optimization setting, o...
ICANN
2011
Springer
13 years 2 months ago
2011
Springer
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
TCS
2011
13 years 6 months ago
2011
The PAC-learning model is distribution-independent in the sense that the learner must reach a learning goal with a limited number of labeled random examples without any prior know...
TASLP
2011
13 years 6 months ago
2011
—This paper presents a novel student model intended to automate word-list-based reading assessments in a classroom setting, specifically for a student population that includes b...
ICDM
2010
IEEE
13 years 8 months ago
2010
IEEE
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
CIKM
2010
Springer
13 years 8 months ago
2010
Springer
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
ECCV
2010
Springer
13 years 10 months ago
2010
Springer
Compressive sampling (CS) is aimed at acquiring a signal or image from data which is deemed insufficient by Nyquist/Shannon sampling theorem. Its main idea is to recover a signal ...
CSL
2010
Springer
13 years 10 months ago
2010
Springer
The voice activity detectors (VADs) based on statistical models have shown impressive performances especially when fairly precise statistical models are employed. Moreover, the ac...
PAMI
2000
13 years 11 months ago
2000
TNN
2008
13 years 11 months ago
2008
In this paper, a supervised neural network training technique based on constrained optimization is developed for preserving prior knowledge of an input