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JMLR
2012
6 years 12 months ago
Beyond Logarithmic Bounds in Online Learning
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...
Francesco Orabona, Nicolò Cesa-Bianchi, Cla...
ICANN
2011
Springer
8 years 27 days ago
Learning from Multiple Annotators with Gaussian Processes
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...
Perry Groot, Adriana Birlutiu, Tom Heskes
TCS
2011
8 years 4 months ago
Smart PAC-learners
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...
Malte Darnstädt, Hans-Ulrich Simon
TASLP
2011
8 years 4 months ago
A Generative Student Model for Scoring Word Reading Skills
—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...
Joseph Tepperman, Sungbok Lee, Shrikanth Narayanan...
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
8 years 6 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
CIKM
2010
Springer
8 years 6 months ago
Regularization and feature selection for networked features
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, ...
Hongliang Fei, Brian Quanz, Jun Huan
ECCV
2010
Springer
8 years 8 months ago
Hybrid Compressive Sampling via a New Total Variation TVL1
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 ...
Xianbiao Shu, Narendra Ahuja
CSL
2010
Springer
8 years 8 months ago
Voice activity detection based on statistical models and machine learning approaches
The voice activity detectors (VADs) based on statistical models have shown impressive performances especially when fairly precise statistical models are employed. Moreover, the ac...
Jong Won Shin, Joon-Hyuk Chang, Nam Soo Kim
PAMI
2000
95views more  PAMI 2000»
8 years 9 months ago
Boundary Finding with Prior Shape and Smoothness Models
Yongmei Wang, Lawrence H. Staib
TNN
2008
95views more  TNN 2008»
8 years 9 months ago
A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training
In this paper, a supervised neural network training technique based on constrained optimization is developed for preserving prior knowledge of an input
Silvia Ferrari, Mark Jensenius
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