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» A theory of learning with similarity functions
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ICML
2009
IEEE
16 years 2 months ago
Learning structurally consistent undirected probabilistic graphical models
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...
Sushmita Roy, Terran Lane, Margaret Werner-Washbur...
ECCV
2008
Springer
16 years 3 months ago
Local Regularization for Multiclass Classification Facing Significant Intraclass Variations
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
Lior Wolf, Yoni Donner
EUROCOLT
1995
Springer
15 years 5 months ago
The structure of intrinsic complexity of learning
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
Sanjay Jain, Arun Sharma
PLDI
2010
ACM
15 years 6 months ago
Resolving and exploiting the k-CFA paradox: illuminating functional vs. object-oriented program analysis
Low-level program analysis is a fundamental problem, taking the shape of “flow analysis” in functional languages and “points-to” analysis in imperative and object-oriente...
Matthew Might, Yannis Smaragdakis, David Van Horn
CSDA
2006
84views more  CSDA 2006»
15 years 1 months ago
Performing hypothesis tests on the shape of functional data
We explore different approaches for performing hypothesis tests on the shape of a mean function by developing general methodologies both, for the often assumed, i.i.d. error struc...
Gareth M. James, Ashish Sood