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Property testing and its connection to learning and approximation
In this paper, we consider the question of determining whether a function <italic>f</italic> has property P or is ε-far from any function with property P. A <italic>property testing</italic>Expand
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The power of amnesia: Learning probabilistic automata with variable memory length
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic finite automata which we nameExpand
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Property Testing in Bounded Degree Graphs
We further develop the study of testing graph properties as initiated by Goldreich, Goldwasser and Ron. Loosely speaking, given an oracle access to a graph, we wish to distinguish the case when theExpand
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On the learnability of discrete distributions
We introduce and investigate a new model of learning probability distributions from independent draws. Our model is inspired by the popular Probably Approximately Correct (PAC) model for learningExpand
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On Testing Expansion in Bounded-Degree Graphs
We consider testing graph expansion in the bounded-degree graph model. Specifically, we refer to algorithms for testing whether the graph has a second eigenvalue bounded above by a given threshold orExpand
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On Approximating the Minimum Vertex Cover in Sublinear Time and the Connection to Distributed Algorithms
  • Michal Parnas, D. Ron
  • Mathematics, Computer Science
  • Electron. Colloquium Comput. Complex.
  • 1 August 2007
For a given graph G over n vertices, let OPT"G denote the size of an optimal solution in G of a particular minimization problem (e.g., the size of a minimum vertex cover). A randomized algorithm willExpand
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Property Testing in Bounded Degree Graphs
AbstractWe further develop the study of testing graph properties as initiated by Goldreich, Goldwasser and Ron. Loosely speaking, given an oracle access to a graph, we wish to distinguish the caseExpand
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The Power of Amnesia
We propose a learning algorithm for a variable memory length Markov process. Human communication, whether given as text, handwriting, or speech, has multi characteristic time scales. On short scalesExpand
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Tolerant property testing and distance approximation
In this paper we study a generalization of standard property testing where the algorithms are required to be more tolerant with respect to objects that do not have, but are close to having, theExpand
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Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation
In this article we prove sanity-check bounds for the error of the leave-oneout cross-validation estimate of the generalization error: that is, bounds showing that the worst-case error of thisExpand
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