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» Learning from Examples and Membership Queries with Structure...
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CIVR
2009
Springer
192views Image Analysis» more  CIVR 2009»
14 years 1 months ago
Example based video filters
Many of the successful multimedia retrieval systems focus on developing efficient and effective video retrieval solutions with the help of appropriate index structures. In these ...
Mihir Jain, Sreekanth Vempati, Chandrika Pulla, C....
IJAR
2010
113views more  IJAR 2010»
13 years 5 months ago
A geometric view on learning Bayesian network structures
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Milan Studený, Jirí Vomlel, Raymond ...
STOC
2009
ACM
120views Algorithms» more  STOC 2009»
14 years 7 months ago
Bit-probe lower bounds for succinct data structures
We prove lower bounds on the redundancy necessary to represent a set S of objects using a number of bits close to the information-theoretic minimum log2 |S|, while answering vario...
Emanuele Viola
ICDCS
1995
IEEE
13 years 10 months ago
Specifying Weak Sets
nt formal speci cations of a new abstraction, weak sets, which can be used to alleviate high latencies when retrieving data from a wide-area information system like the World Wide...
Jeannette M. Wing, David C. Steere
GLOBECOM
2008
IEEE
14 years 1 months ago
A Memory-Optimized Bloom Filter Using an Additional Hashing Function
— A Bloom filter is a simple space-efficient randomized data structure for the representation set of items in order to support membership queries. In recent years, Bloom filte...
Mahmood Ahmadi, Stephan Wong