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» Informative sampling for large unbalanced data sets
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ISMIR
2005
Springer
150views Music» more  ISMIR 2005»
15 years 9 months ago
A Bootstrap Method for Training an Accurate Audio Segmenter
Supervised learning can be used to create good systems for note segmentation in audio data. However, this requires a large set of labeled training examples, and handlabeling is qu...
Ning Hu, Roger B. Dannenberg
142
Voted
SIGMOD
2012
ACM
240views Database» more  SIGMOD 2012»
13 years 6 months ago
Finding related tables
We consider the problem of finding related tables in a large corpus of heterogenous tables. Detecting related tables provides users a powerful tool for enhancing their tables wit...
Anish Das Sarma, Lujun Fang, Nitin Gupta 0003, Alo...
154
Voted
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 6 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
CLOR
2006
15 years 7 months ago
Shared Features for Multiclass Object Detection
Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
147
Voted
SIGMETRICS
2008
ACM
111views Hardware» more  SIGMETRICS 2008»
15 years 3 months ago
Predicting the resource consumption of network intrusion detection systems
Abstract. When installing network intrusion detection systems (NIDSs), operators are faced with a large number of parameters and analysis options for tuning trade-offs between dete...
Holger Dreger, Anja Feldmann, Vern Paxson, Robin S...