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» On learning with dissimilarity functions
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CORR
2010
Springer
70views Education» more  CORR 2010»
13 years 9 months ago
Structured sparsity-inducing norms through submodular functions
Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
Francis Bach
JMLR
2010
187views more  JMLR 2010»
13 years 4 months ago
SFO: A Toolbox for Submodular Function Optimization
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
Andreas Krause
IACR
2011
115views more  IACR 2011»
12 years 9 months ago
Pseudorandom Functions and Lattices
We give direct constructions of pseudorandom function (PRF) families based on conjectured hard lattice problems and learning problems. Our constructions are asymptotically effici...
Abhishek Banerjee, Chris Peikert, Alon Rosen
ALT
2003
Springer
14 years 6 months ago
Intrinsic Complexity of Uniform Learning
Inductive inference is concerned with algorithmic learning of recursive functions. In the model of learning in the limit a learner successful for a class of recursive functions mus...
Sandra Zilles
MLDM
2007
Springer
14 years 3 months ago
Outlier Detection with Kernel Density Functions
Abstract. Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detec...
Longin Jan Latecki, Aleksandar Lazarevic, Dragolju...