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» On learning with dissimilarity functions
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EMNLP
2011
14 years 6 months ago
Relation Extraction with Relation Topics
This paper describes a novel approach to the semantic relation detection problem. Instead of relying only on the training instances for a new relation, we leverage the knowledge l...
Chang Wang, James Fan, Aditya Kalyanpur, David Gon...
RECOMB
2012
Springer
13 years 9 months ago
Estimating the Accuracy of Multiple Alignments and its Use in Parameter Advising
We develop a novel and general approach to estimating the accuracy of protein multiple sequence alignments without knowledge of a reference alignment, and use our approach to addre...
Dan F. DeBlasio, Travis J. Wheeler, John D. Kececi...
ICFP
2008
ACM
16 years 7 months ago
Write it recursively: a generic framework for optimal path queries
Optimal path queries are queries to obtain an optimal path specified by a given criterion of optimality. There have been many studies to give efficient algorithms for classes of o...
Akimasa Morihata, Kiminori Matsuzaki, Masato Takei...
IJCNN
2006
IEEE
16 years 1 months ago
Venn-like models of neo-cortex patches
— This work presents a new architecture of artificial neural networks – Venn Networks, which produce localized activations in a 2D map while executing simple cognitive tasks. T...
Fernando Buarque de Lima Neto, Philippe De Wilde
AIPS
2008
15 years 9 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan