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» Algorithms for discovering bucket orders from data
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121
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KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 4 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
130
Voted
ACCV
2010
Springer
15 years 3 months ago
Identifying Surprising Events in Videos Using Bayesian Topic Models
Automatic processing of video data is essential in order to allow efficient access to large amounts of video content, a crucial point in such applications as video mining and surve...
Avishai Hendel, Daphna Weinshall, Shmuel Peleg
113
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DMIN
2007
186views Data Mining» more  DMIN 2007»
15 years 2 months ago
Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
- The classifier built from a data set with a highly skewed class distribution generally predicts the more frequently occurring classes much more often than the infrequently occurr...
Gary M. Weiss, Kate McCarthy, Bibi Zabar
121
Voted
UAI
1996
15 years 2 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
106
Voted
CORR
2010
Springer
163views Education» more  CORR 2010»
15 years 24 days ago
Distributed Principal Component Analysis for Wireless Sensor Networks
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
Yann-Aël Le Borgne, Sylvain Raybaud, Gianluca...