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ALT
1999
Springer
14 years 11 days ago
PAC Learning with Nasty Noise
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
Nader H. Bshouty, Nadav Eiron, Eyal Kushilevitz
ICDM
2007
IEEE
184views Data Mining» more  ICDM 2007»
14 years 2 months ago
Bayesian Folding-In with Dirichlet Kernels for PLSI
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
ICCV
2009
IEEE
15 years 1 months ago
An Algebraic Approach to Affine Registration of Point Sets
This paper proposes a new affine registration algorithm for matching two point sets in IR2 or IR3. The input point sets are represented as probability density functions, using e...
Jeffrey Ho, Adrian Peter, Anand Rangarajan, Ming-H...
JMLR
2012
11 years 10 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
FTDCS
2003
IEEE
14 years 1 months ago
On-Demand Media Streaming Over the Internet
We propose a new model for on-demand media streaming centered around the peer-to-peer (P2P) paradigm. The proposed P2P model can support a large number of clients with a low overa...
Mohamed Hefeeda, Bharat K. Bhargava