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[کتاب][B] Analysis of boolean functions
R O'Donnell - 2014 - books.google.com
Boolean functions are perhaps the most basic objects of study in theoretical computer
science. They also arise in other areas of mathematics, including combinatorics, statistical …
science. They also arise in other areas of mathematics, including combinatorics, statistical …
Discriminative K-SVD for dictionary learning in face recognition
In a sparse-representation-based face recognition scheme, the desired dictionary should
have good representational power (ie, being able to span the subspace of all faces) while …
have good representational power (ie, being able to span the subspace of all faces) while …
[کتاب][B] Boolean functions: Theory, algorithms, and applications
Y Crama, PL Hammer - 2011 - books.google.com
Written by prominent experts in the field, this monograph provides the first comprehensive,
unified presentation of the structural, algorithmic and applied aspects of the theory of …
unified presentation of the structural, algorithmic and applied aspects of the theory of …
Agnostic learning of monomials by halfspaces is hard
We prove the following strong hardness result for learning: Given a distribution of labeled
examples from the hypercube such that there exists a monomial consistent with (1-ϵ) of the …
examples from the hypercube such that there exists a monomial consistent with (1-ϵ) of the …
Understanding influence functions and datamodels via harmonic analysis
Influence functions estimate effect of individual data points on predictions of the model on
test data and were adapted to deep learning in Koh and Liang [2017]. They have been used …
test data and were adapted to deep learning in Koh and Liang [2017]. They have been used …
Bounded independence fools halfspaces
We show that any distribution on {-1,+1\}^n that is k-wise independent fools any halfspace
(or linear threshold function) h:{-1,+1\}^n→{-1,+1\}, ie, any function of the form …
(or linear threshold function) h:{-1,+1\}^n→{-1,+1\}, ie, any function of the form …
Property testing: A learning theory perspective
D Ron - Foundations and Trends® in Machine Learning, 2008 - nowpublishers.com
Property testing deals with tasks where the goal is to distinguish between the case that an
object (eg, function or graph) has a prespecified property (eg, the function is linear or the …
object (eg, function or graph) has a prespecified property (eg, the function is linear or the …
Testing Fourier dimensionality and sparsity
We present a range of new results for testing properties of Boolean functions that are
defined in terms of the Fourier spectrum. Broadly speaking, our results show that the …
defined in terms of the Fourier spectrum. Broadly speaking, our results show that the …
New algorithms and lower bounds for monotonicity testing
We consider the problem of testing whether an unknown Boolean function f:{-1, 1} n→{-1, 1}
is monotone versus ε-far from every monotone function. The two main results of this paper …
is monotone versus ε-far from every monotone function. The two main results of this paper …
A polynomial lower bound for testing monotonicity
We show that every algorithm for testing n-variate Boolean functions for monotonicityhas
query complexity Ω (n 1/4). All previous lower bounds for this problem were designed for …
query complexity Ω (n 1/4). All previous lower bounds for this problem were designed for …