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IPMI
2007
Springer
16 years 7 months ago
Adaptive Time-Frequency Models for Single-Trial M/EEG Analysis
Abstract. A new method is introduced for estimating single-trial magnetoor electro-encephalography (M/EEG), based on a non-linear fit of timefrequency atoms. The method can be appl...
Christian Bénar, Maureen Clerc, Théo...
ICML
2009
IEEE
16 years 7 months ago
Robust feature extraction via information theoretic learning
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
Xiaotong Yuan, Bao-Gang Hu
ICML
2001
IEEE
16 years 7 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
ICML
1996
IEEE
16 years 7 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman
ISBI
2004
IEEE
16 years 7 months ago
A Template-Propagation Method for Segmentation of Filamentous Structures in Electron Tomograms
We report a method for semi-automated segmentation of extended features such as filamentous structures in electron tomograms. We present an application of this method for the auto...
Sriram Subramaniam, Peijun Zhang, David Germain, T...