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» Learning from Skewed Class Multi-relational Databases
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ICASSP
2010
IEEE
13 years 7 months ago
Multiple sequence alignment based bootstrapping for improved incremental word learning
We investigate incremental word learning with few training examples in a Hidden Markov Model (HMM) framework suitable for an interactive learning scenario with little prior knowle...
Irene Ayllól Clemente, Martin Heckmann, Ger...
PODS
2009
ACM
100views Database» more  PODS 2009»
14 years 9 months ago
Space-optimal heavy hitters with strong error bounds
The problem of finding heavy hitters and approximating the frequencies of items is at the heart of many problems in data stream analysis. It has been observed that several propose...
Radu Berinde, Graham Cormode, Piotr Indyk, Martin ...
SIGIR
2005
ACM
14 years 2 months ago
A database centric view of semantic image annotation and retrieval
We introduce a new model for semantic annotation and retrieval from image databases. The new model is based on a probabilistic formulation that poses annotation and retrieval as c...
Gustavo Carneiro, Nuno Vasconcelos
IUI
2003
ACM
14 years 1 months ago
Towards a theory of natural language interfaces to databases
The need for Natural Language Interfaces to databases (NLIs) has become increasingly acute as more and more people access information through their web browsers, PDAs, and cell ph...
Ana-Maria Popescu, Oren Etzioni, Henry A. Kautz
KDD
2004
ACM
113views Data Mining» more  KDD 2004»
14 years 8 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...