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» Learning of Boolean Functions Using Support Vector Machines
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ICST
2009
IEEE
14 years 2 months ago
Using JML Runtime Assertion Checking to Automate Metamorphic Testing in Applications without Test Oracles
It is challenging to test applications and functions for which the correct output for arbitrary input cannot be known in advance, e.g. some computational science or machine learni...
Christian Murphy, Kuang Shen, Gail E. Kaiser
ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
14 years 2 months ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa
NECO
2007
115views more  NECO 2007»
13 years 7 months ago
Training Recurrent Networks by Evolino
In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
Jürgen Schmidhuber, Daan Wierstra, Matteo Gag...
ICCV
2003
IEEE
14 years 9 months ago
Recognition with Local Features: the Kernel Recipe
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...
AIRS
2005
Springer
14 years 1 months ago
VisMed: A Visual Vocabulary Approach for Medical Image Indexing and Retrieval
Voluminous medical images are generated daily. They are critical assets for medical diagnosis, research, and teaching. To facilitate automatic indexing and retrieval of large medic...
Joo-Hwee Lim, Jean-Pierre Chevallet