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IDEAL
2010
Springer
14 years 9 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
CVPR
2012
IEEE
13 years 1 months ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
ICDM
2008
IEEE
190views Data Mining» more  ICDM 2008»
15 years 5 months ago
Simultaneous Co-segmentation and Predictive Modeling for Large, Temporal Marketing Data
Several marketing problems involve prediction of customer purchase behavior and forecasting future preferences. We consider predictive modeling of large scale, bi-modal or multimo...
Meghana Deodhar, Joydeep Ghosh
ML
2006
ACM
15 years 5 months ago
ML grid programming with ConCert
Grid computing has become increasingly popular with the growth of the Internet, especially in large-scale scientific computation. Computational Grids are characterized by their s...
Tom Murphy VII
AUSAI
2005
Springer
15 years 4 months ago
Adaptive Utility-Based Scheduling in Resource-Constrained Systems
This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework fo...
David Vengerov