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ICML
2003
IEEE
16 years 2 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
AAAI
2012
13 years 3 months ago
Relative Attributes for Enhanced Human-Machine Communication
We propose to model relative attributes1 that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can captur...
Devi Parikh, Adriana Kovashka, Amar Parkash, Krist...
ICTAI
2007
IEEE
15 years 7 months ago
Constructing VEGGIE: Machine Learning for Context-Sensitive Graph Grammars
Context-sensitive graph grammar construction tools have been used to develop and study interesting languages. However, the high dimensionality of graph grammars result in costly e...
Keven Ates, Kang Zhang
ICML
2007
IEEE
16 years 2 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
ALT
2004
Springer
15 years 10 months ago
Learning r-of-k Functions by Boosting
We investigate further improvement of boosting in the case that the target concept belongs to the class of r-of-k threshold Boolean functions, which answer “+1” if at least r o...
Kohei Hatano, Osamu Watanabe