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» On a theory of learning with similarity functions
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ICML
2009
IEEE
16 years 19 days 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 1 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 3 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 4 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»
14 years 12 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