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NIPS
1994
13 years 10 months ago
From Data Distributions to Regularization in Invariant Learning
Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing...
Todd K. Leen
AIME
2007
Springer
14 years 3 months ago
A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data
Abstract. The practice of medicine is becoming increasingly evidencebased and clinical practice guidelines (CPGs) are necessary for advancing evidence-based medicine (EBM). We hypo...
Subramani Mani, Constantin F. Aliferis
JMLR
2008
104views more  JMLR 2008»
13 years 8 months ago
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new cl...
Giorgio Corani, Marco Zaffalon
GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
14 years 1 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
WAIM
2010
Springer
14 years 1 months ago
Semi-supervised Learning from Only Positive and Unlabeled Data Using Entropy
Abstract. The problem of classification from positive and unlabeled examples attracts much attention currently. However, when the number of unlabeled negative examples is very sma...
Xiaoling Wang, Zhen Xu, Chaofeng Sha, Martin Ester...