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Exact Pairs and Uniform Upper Bounds
, 2009
"... A (Turing) ideal I is a downward closed set of Turing degrees which is also closed under the supremum operation. Countable ideals have played interesting roles in the studies of global apsects of the partial order of Turing degrees, and also in early development of fine structure theory of Gödel’s ..."
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constructible universe. Uniform upper bounds and exact pairs are two useful notions in studying countable ideals. They reduce countable ideals which are sets of Turing degrees to finite tuples of Turing degrees. Previous works have shown that these two notions are very closed and lead to further questions
ELECTRONIC COMMUNICATIONS in PROBABILITY UNIFORM UPPER BOUND
, 1998
"... The authors of [1] stated the following conjecture: Let µ be a symmetric αstable measure on a separable Banach space and B acenteredballsuchthatµ(B) ≤ b. Then there exists a constant R(b), depending only on b, such that µ(tB) ≤ R(b)tµ(B) for all 0 <t<1. We prove that the above inequality ho ..."
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The authors of [1] stated the following conjecture: Let µ be a symmetric αstable measure on a separable Banach space and B acenteredballsuchthatµ(B) ≤ b. Then there exists a constant R(b), depending only on b, such that µ(tB) ≤ R(b)tµ(B) for all 0 <t<1. We prove that the above inequality holds but the constant R must depend also on α. Recently, the authors of [1] proved the following (Theorem 6.4 in [1]): Let µ be a symmetric αstable measure, 0 <α ≤ 2, on a separable Banach space, fix b<1, and let B denote a centered ball such that µ(B) ≤ b. Then there exists a constant R(b) = 3 b √ 1−b, depending only on b, such that for all 0 ≤ t ≤ 1 µ(tB) ≤ R(b)t α/2 µ(B). (1) Of course, for small values of t, thequantityt α/2 is much larger than t. The authors of [1] stated in their Conjecture 7.4 that (1) is true for all symmetric αstable measures with t instead of t α/2 and some R(b) depending only on b. In our earlier paper [3], we also gave an estimate of a stable measure of a small ball. Namely,
Phase separation in random cluster models I: uniform upper bounds on local deviation
, 1001
"... This is the first in a series of three papers that addresses the behaviour of the droplet that results, in the percolating phase, from conditioningthe planarFortuinKasteleynrandomcluster model on the presence of an open dual circuit Γ0 encircling the origin and enclosing an area of at least (or exa ..."
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Cited by 4 (2 self)
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This is the first in a series of three papers that addresses the behaviour of the droplet that results, in the percolating phase, from conditioningthe planarFortuinKasteleynrandomcluster model on the presence of an open dual circuit Γ0 encircling the origin and enclosing an area of at least (or exactly) n 2. (By the FortuinKasteleyn representation, the model is a close relative of the droplet formed by conditioning the Potts model on an excess of spins of a given type.) We consider local deviation of the droplet boundary, measured in a radial sense by the maximum local roughness, MLR () Γ0, this being the maximum distance from a point in the circuit Γ0 to the boundary ∂conv () Γ0 of the circuit’s convex hull; and in a longitudinal sense by what we term maximum facet length, MFL () Γ0, namely, the length of the longest line segment of which the polygon ∂conv () Γ0 is formed. The principal conclusion of the series of papers is the
A UNIFORM UPPER BOUND FOR THE CHARACTER DEGREE SUMS AND GELFANDGRAEVLIKE CHARACTERS FOR FINITE SIMPLE GROUPS
"... ar ..."
A Partial KArboretum of Graphs With Bounded Treewidth
 J. Algorithms
, 1998
"... The notion of treewidth has seen to be a powerful vehicle for many graph algorithmic studies. This survey paper wants to give an overview of many classes of graphs that can be seen to have a uniform upper bound on the treewidth of graphs in the class. Also, some mutual relations between such classes ..."
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Cited by 328 (34 self)
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The notion of treewidth has seen to be a powerful vehicle for many graph algorithmic studies. This survey paper wants to give an overview of many classes of graphs that can be seen to have a uniform upper bound on the treewidth of graphs in the class. Also, some mutual relations between
PROBABILITY INEQUALITIES FOR SUMS OF BOUNDED RANDOM VARIABLES
, 1962
"... Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges of the s ..."
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Cited by 2217 (2 self)
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Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges
A Limited Memory Algorithm for Bound Constrained Optimization
 SIAM Journal on Scientific Computing
, 1994
"... An algorithm for solving large nonlinear optimization problems with simple bounds is described. ..."
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Cited by 557 (9 self)
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An algorithm for solving large nonlinear optimization problems with simple bounds is described.
A Scheme for RealTime Channel Establishment in WideArea Networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1990
"... Multimedia communication involving digital audio and/or digital video has rather strict delay requirements. A realtime channel is defined in this paper as a simplex connection between a source and a destination characterized by parameters representing the performance requirements of the client. A r ..."
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Cited by 710 (31 self)
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realtime service is capable of creating realtime channels on demand and guaranteeing their performance. These guarantees often take the form of lower bounds on the bandwidth allocated to a channel and upper bounds on the delays to be experienced by a packet on the channel. In this paper
Boosting a Weak Learning Algorithm By Majority
, 1995
"... We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses, each of which is generated by training the given learning algorithm on a different set of examples. Our algorithm is based on ideas pr ..."
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Cited by 516 (15 self)
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presented by Schapire in his paper "The strength of weak learnability", and represents an improvement over his results. The analysis of our algorithm provides general upper bounds on the resources required for learning in Valiant's polynomial PAC learning framework, which are the best general
Results 1  10
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1,638,892