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ML
2002
ACM
178views Machine Learning» more  ML 2002»
13 years 7 months ago
Metric-Based Methods for Adaptive Model Selection and Regularization
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Dale Schuurmans, Finnegan Southey
UAI
1996
13 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
ICML
2009
IEEE
14 years 8 months ago
Online dictionary learning for sparse coding
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
CVPR
2009
IEEE
15 years 2 months ago
Active Volume Models for 3D Medical Image Segmentation
In this paper, we propose a novel predictive model for object boundary, which can integrate information from any sources. The model is a dynamic “object” model whose manifes...
Tian Shen (Lehigh University), Hongsheng Li (Lehig...
RAID
2010
Springer
13 years 6 months ago
A Data-Centric Approach to Insider Attack Detection in Database Systems
The insider threat against database management systems is a dangerous security problem. Authorized users may abuse legitimate privileges to masquerade as other users or to maliciou...
Sunu Mathew, Michalis Petropoulos, Hung Q. Ngo, Sh...