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» Iterative Improvement of Neural Classifiers
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ACCV
2009
Springer
15 years 4 months ago
Evolving Mean Shift with Adaptive Bandwidth: A Fast and Noise Robust Approach
Abstract. This paper presents a novel nonparametric clustering algorithm called evolving mean shift (EMS) algorithm. The algorithm iteratively shrinks a dataset and generates well ...
Qi Zhao, Zhi Yang, Hai Tao, Wentai Liu
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
15 years 10 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
CVPR
2010
IEEE
15 years 6 months ago
Far-Sighted Active Learning on a Budget for Image and Video Recognition
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
Sudheendra Vijayanarasimhan, Prateek Jain, Kristen...
ICCV
2007
IEEE
15 years 11 months ago
A 3D Teacher for Car Detection in Aerial Images
This paper demonstrates how to reduce the hand labeling effort considerably by 3D information in an object detection task. In particular, we demonstrate how an efficient car detec...
Stefan Kluckner, Georg Pacher, Helmut Grabner, Hor...
KDD
2003
ACM
114views Data Mining» more  KDD 2003»
15 years 10 months ago
Information awareness: a prospective technical assessment
Recent proposals to apply data mining systems to problems in law enforcement, national security, and fraud detection have attracted both media attention and technical critiques of...
David Jensen, Matthew J. Rattigan, Hannah Blau