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» On learning with dissimilarity functions
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EMNLP
2011
12 years 8 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
11 years 10 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
14 years 8 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
14 years 2 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
13 years 10 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