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» On the Learnability of Vector Spaces
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ECCV
2010
Springer
15 years 3 months ago
3D Point Correspondence by Minimum Description Length in Feature Space
Abstract. Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence ...
COLT
2001
Springer
15 years 2 months ago
Limitations of Learning via Embeddings in Euclidean Half-Spaces
The notion of embedding a class of dichotomies in a class of linear half spaces is central to the support vector machines paradigm. We examine the question of determining the mini...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
ICIP
2010
IEEE
14 years 7 months ago
Combining free energy score spaces with information theoretic kernels: Application to scene classification
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Manuele Bicego, Alessandro Perina, Vittorio Murino...
SCALESPACE
2005
Springer
15 years 3 months ago
Discrete Representation of Top Points via Scale Space Tessellation
In previous work, singular points (or top points) in the scale space representation of generic images have proven valuable for image matching. In this paper, we propose a construct...
Bram Platel, M. Fatih Demirci, Ali Shokoufandeh, L...
FOCS
2009
IEEE
15 years 4 months ago
The Data Stream Space Complexity of Cascaded Norms
Abstract— We consider the problem of estimating cascaded aggregates over a matrix presented as a sequence of updates in a data stream. A cascaded aggregate P ◦Q is defined by ...
T. S. Jayram, David P. Woodruff