Finding latent factors of the data using matrix factorizations is a tried-and-tested approach in data mining. But finding shared factors over multiple matrices is more novel prob...
Non-negative matrix factorisation (NMF) is an unsupervised learning technique that decomposes a non-negative data matrix into a product of two lower rank non-negative matrices. Th...
Alexander Bertrand, Kris Demuynck, Veronique Stout...
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
This paper describes an autonomous vision system for realization of tasks consist of following a person with a mobile robot as well as interpreting some static and dynamic command...
The paper addresses object localization via a distributed sensor network. A centralized estimation approach is undertaken along with a selective node activation strategy to ensure...