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AAAI
2011
14 years 7 months ago
Relational Blocking for Causal Discovery
Blocking is a technique commonly used in manual statistical analysis to account for confounding variables. However, blocking is not currently used in automated learning algorithms...
Matthew J. Rattigan, Marc E. Maier, David Jensen
205
Voted
CVPR
1997
IEEE
15 years 11 months ago
Learning Generic Prior Models for Visual Computation
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
Song Chun Zhu, David Mumford
CSL
2008
Springer
15 years 7 months ago
A stopping criterion for active learning
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...
Andreas Vlachos
ECCV
2008
Springer
16 years 9 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
KDD
2012
ACM
212views Data Mining» more  KDD 2012»
13 years 9 months ago
Factoring past exposure in display advertising targeting
Online advertising is increasingly becoming more performance oriented, where the decision to show an advertisement to a user is made based on the user’s propensity to respond to...
Neha Gupta, Abhimanyu Das, Sandeep Pandey, Vijay K...