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» On Deterministic Approximation of DNF
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MOC
2000
86views more  MOC 2000»
13 years 7 months ago
Numerical algorithms for semilinear parabolic equations with small parameter based on approximation of stochastic equations
The probabilistic approach is used for constructing special layer methods to solve the Cauchy problem for semilinear parabolic equations with small parameter. Despite their probabi...
G. N. Milstein, M. V. Tretyakov
ANCS
2009
ACM
13 years 5 months ago
Divide and discriminate: algorithm for deterministic and fast hash lookups
Exact and approximate membership lookups are among the most widely used primitives in a number of network applications. Hash tables are commonly used to implement these primitive ...
Domenico Ficara, Stefano Giordano, Sailesh Kumar, ...
COLT
2007
Springer
14 years 1 months ago
Property Testing: A Learning Theory Perspective
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Dana Ron
COLT
2003
Springer
14 years 27 days ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio
IJCAI
2007
13 years 9 months ago
Learning from Partial Observations
We present a general machine learning framework for modelling the phenomenon of missing information in data. We propose a masking process model to capture the stochastic nature of...
Loizos Michael