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ICML
2004
IEEE
14 years 25 days 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
ICPR
2006
IEEE
14 years 8 months ago
Graph-based transformation manifolds for invariant pattern recognition with kernel methods
We present here an approach for applying the technique of modeling data transformation manifolds for invariant learning with kernel methods. The approach is based on building a ke...
Alexei Pozdnoukhov, Samy Bengio
CIDM
2007
IEEE
13 years 11 months ago
Efficient Kernel-based Learning for Trees
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
AI
2010
Springer
13 years 7 months ago
Kernel functions for case-based planning
Case-based planning can take advantage of former problem-solving experiences by storing in a plan library previously generated plans that can be reused to solve similar planning p...
Ivan Serina
NIPS
2001
13 years 8 months ago
Convolution Kernels for Natural Language
We describe the application of kernel methods to Natural Language Processing (NLP) problems. In many NLP tasks the objects being modeled are strings, trees, graphs or other discre...
Michael Collins, Nigel Duffy