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GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
16 years 1 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classiï...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
15 years 4 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
CVPR
2012
IEEE
13 years 12 months ago
Stream-based Joint Exploration-Exploitation Active Learning
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
MLDM
2009
Springer
16 years 1 months ago
Drift-Aware Ensemble Regression
Abstract. Regression models are often required for controlling production processes by predicting parameter values. However, the implicit assumption of standard regression techniqu...
Frank Rosenthal, Peter Benjamin Volk, Martin Hahma...
ICML
2010
IEEE
15 years 7 months ago
3D Convolutional Neural Networks for Human Action Recognition
We consider the fully automated recognition of actions in uncontrolled environment. Most existing work relies on domain knowledge to construct complex handcrafted features from in...
Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu