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ICPR
2010
IEEE
15 years 4 months ago
Data-Driven Lung Nodule Models for Robust Nodule Detection in Chest CT
The quality of the lung nodule models determines the success of lung nodule detection. This paper describes aspects of our data-driven approach for modeling lung nodules using the...
Amal Farag, James Graham, Aly A. Farag
129
Voted
ICANN
2007
Springer
15 years 11 months ago
Structure Learning with Nonparametric Decomposable Models
Abstract. We present a novel approach to structure learning for graphical models. By using nonparametric estimates to model clique densities in decomposable models, both discrete a...
Anton Schwaighofer, Mathäus Dejori, Volker Tr...
131
Voted
ESANN
2008
15 years 6 months ago
A Method for Time Series Prediction using a Combination of Linear Models
This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
David Martínez-Rego, Oscar Fontenla-Romero,...
IJCNN
2008
IEEE
15 years 11 months ago
Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Shijian Lu, Cuntai Guan, Haihong Zhang
JMLR
2012
13 years 7 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey