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ICML
2004
IEEE
14 years 2 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
IJDMB
2008
128views more  IJDMB 2008»
13 years 9 months ago
Protein homology detection with biologically inspired features and interpretable statistical models
: Computational classification of proteins using methods such as string kernels and Fisher-SVM has demonstrated great success. However, the resulting models do not offer an immedia...
Pai-Hsi Huang, Vladimir Pavlovic
IJIS
2011
83views more  IJIS 2011»
13 years 20 days ago
Conceptual modeling in full computation-tree logic with sequence modal operator
In this paper, we propose a method for modeling concepts in full computation-tree logic with sequence modal operators. An extended full computation-tree logic, CTLS∗ , is introdu...
Ken Kaneiwa, Norihiro Kamide
EMNLP
2010
13 years 7 months ago
An Efficient Algorithm for Unsupervised Word Segmentation with Branching Entropy and MDL
This paper proposes a fast and simple unsupervised word segmentation algorithm that utilizes the local predictability of adjacent character sequences, while searching for a leaste...
Valentin Zhikov, Hiroya Takamura, Manabu Okumura
NIPS
2004
13 years 10 months ago
Joint MRI Bias Removal Using Entropy Minimization Across Images
The correction of bias in magnetic resonance images is an important problem in medical image processing. Most previous approaches have used a maximum likelihood method to increase...
Erik G. Learned-Miller, Parvez Ahammad