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IDEAL
2010
Springer
15 years 2 months ago
Dimension Reduction for Regression with Bottleneck Neural Networks
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
Elina Parviainen
CORR
2011
Springer
199views Education» more  CORR 2011»
14 years 11 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...
ICASSP
2011
IEEE
14 years 8 months ago
Approximation of pattern transformation manifolds with parametric dictionaries
The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...
Elif Vural, Pascal Frossard
KDD
2007
ACM
154views Data Mining» more  KDD 2007»
16 years 4 months ago
Canonicalization of database records using adaptive similarity measures
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
Aron Culotta, Michael L. Wick, Robert Hall, Matthe...
DBPL
1999
Springer
98views Database» more  DBPL 1999»
15 years 8 months ago
Ozone: Integrating Structured and Semistructured Data
Applications have an increasing need to manage semistructured data such as data encoded in XML along with conventional structured data. We extend the structured object database ...
Tirthankar Lahiri, Serge Abiteboul, Jennifer Widom