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IJCNN
2006
IEEE
15 years 8 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö
NIPS
2004
15 years 3 months ago
Non-Local Manifold Tangent Learning
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
Yoshua Bengio, Martin Monperrus
123
Voted
ICA
2007
Springer
15 years 6 months ago
Phase-Aware Non-negative Spectrogram Factorization
Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixtur...
R. Mitchell Parry, Irfan A. Essa
ICCV
2011
IEEE
14 years 2 months ago
Discriminative Learning of Relaxed Hierarchy for Large-scale Visual Recognition
In the real visual world, the number of categories a classifier needs to discriminate is on the order of hundreds or thousands. For example, the SUN dataset [24] contains 899 sce...
Tianshi Gao, Daphne Koller
SMC
2007
IEEE
120views Control Systems» more  SMC 2007»
15 years 8 months ago
A data-dependent distance measure for transductive instance-based learning
— We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labe...
Jared Lundell, Dan Ventura