Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
Finding icebergs ? items whose frequency of occurrence is above a certain threshold ? is an important problem with a wide range of applications. Most of the existing work focuses ...
The use of threads is becoming commonplace in both sequential and parallel programs. This paper describes our design and initial experience with non-trace based performance instru...
The success of groupware software largely depends on its capability for being reused in different collaborative scenarios without requiring significant software development effort...
Miguel A. Gomez-Hernandez, Juan I. Asensio-P&eacut...