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176
On Sublinear Convergence
, 1995
"... This note develops a theory of sublinearly converging sequences, including a categorization of the rates of convergence and a method for determining the rate from an iteration function. This report is available by anonymous ftp from thales.cs.umd.edu in the directory pub/reports. y Department o ..."
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Cited by 3 (1 self)
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This note develops a theory of sublinearly converging sequences, including a categorization of the rates of convergence and a method for determining the rate from an iteration function. This report is available by anonymous ftp from thales.cs.umd.edu in the directory pub/reports. y Department
On Sublinear Convergence
, 1995
"... This note develops a theory of sublinearly converging sequences, including a categorization of the rates of convergence and a method for determining the rate from an iteration function. This report is available by anonymous ftp from thales.cs.umd.edu in the directory pub/reports. y Department o ..."
Abstract
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This note develops a theory of sublinearly converging sequences, including a categorization of the rates of convergence and a method for determining the rate from an iteration function. This report is available by anonymous ftp from thales.cs.umd.edu in the directory pub/reports. y Department
Highrate codes with sublineartime decoding
, 2010
"... Locally decodable codes are errorcorrecting codes that admit efficient decoding algorithms; any bit of the original message can be recovered by looking at only a small number of locations of a corrupted codeword. The tradeoff between the rate of a code and the locality/efficiency of its decoding al ..."
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Cited by 8 (0 self)
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Locally decodable codes are errorcorrecting codes that admit efficient decoding algorithms; any bit of the original message can be recovered by looking at only a small number of locations of a corrupted codeword. The tradeoff between the rate of a code and the locality/efficiency of its decoding
Highrate codes with sublineartime decoding
"... Locally decodable codes are errorcorrecting codes that admit efficient decoding algorithms; any bit of the original message can be recovered by looking at only a small number of locations of a corrupted codeword. The tradeoff between the rate of a code and the locality/efficiency of its decoding al ..."
Abstract
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Locally decodable codes are errorcorrecting codes that admit efficient decoding algorithms; any bit of the original message can be recovered by looking at only a small number of locations of a corrupted codeword. The tradeoff between the rate of a code and the locality/efficiency of its decoding
Shift Finding in Sublinear Time
, 2004
"... We study the following basic pattern matching problem. Consider a “code” sequence c consisting of n bits chosen uniformly at random, and a “signal ” sequence x obtained by shifting c (modulo n) and adding noise. The goal is to efficiently recover the shift with high probability. The problem models t ..."
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Cited by 2 (0 self)
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for a random signal (text), even for the case when the error between the signal and the code (pattern) is asymptotically as large as the code size. This is the first sublinear time algorithm for such error rates.
K.; “Darwinian Aspects of Molecular Evolution at Sublinear Propagation Rates
 Bulletin of Mathematical Biology
"... The symmetric distribution and all other states in the symmetry sector of the frequency trajectory increase mean fitness during competitive replication at sublinear propagation rates (parabolic time course). States in the nonsymmetry sector, by contrast, produce negative time variations in mean fit ..."
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Cited by 1 (0 self)
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The symmetric distribution and all other states in the symmetry sector of the frequency trajectory increase mean fitness during competitive replication at sublinear propagation rates (parabolic time course). States in the nonsymmetry sector, by contrast, produce negative time variations in mean
A stochastic gradient method with an exponential convergence rate for finite training sets.
 In NIPS,
, 2012
"... Abstract We propose a new stochastic gradient method for optimizing the sum of a finite set of smooth functions, where the sum is strongly convex. While standard stochastic gradient methods converge at sublinear rates for this problem, the proposed method incorporates a memory of previous gradient ..."
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Cited by 73 (10 self)
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Abstract We propose a new stochastic gradient method for optimizing the sum of a finite set of smooth functions, where the sum is strongly convex. While standard stochastic gradient methods converge at sublinear rates for this problem, the proposed method incorporates a memory of previous gradient
Constant rate PCPs for circuitSAT with sublinear query complexity
, 2013
"... The PCP theorem (Arora et. al., J. ACM 45(1,3)) says that every NPproof can be encoded to another proof, namely, a probabilistically checkable proof (PCP), which can be tested by a verifier that queries only a small part of the PCP. A natural question is how large is the blowup incurred by this en ..."
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that can be checked using n ε queries for circuitSAT instances of size n. Our PCPs have perfect completeness and constant soundness. This is the first constantrate PCP construction that achieves constant soundness with nontrivial query complexity (o(n)). Our proof replaces the lowdegree polynomials
Sublinear Indexing for Large Scale Object Recognition
"... Realistic approaches to large scale object recognition, i.e. for detection and localisation of hundreds or more objects, must support sublinear time indexing. In the paper, we propose a method capable of recognising one of N objects in log(N) time. The ”visual memory ” is organised as a binary deci ..."
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Realistic approaches to large scale object recognition, i.e. for detection and localisation of hundreds or more objects, must support sublinear time indexing. In the paper, we propose a method capable of recognising one of N objects in log(N) time. The ”visual memory ” is organised as a binary
Sublinear Indexing for Large Scale Object Recognition
"... Realistic approaches to large scale object recognition, i.e. for detection and localisation of hundreds or more objects, must support sublinear time indexing. In the paper, we propose a method capable of recognising one of N objects in log(N) time. The ”visual memory ” is organised as a binary deci ..."
Abstract
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Realistic approaches to large scale object recognition, i.e. for detection and localisation of hundreds or more objects, must support sublinear time indexing. In the paper, we propose a method capable of recognising one of N objects in log(N) time. The ”visual memory ” is organised as a binary
Results 1  10
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176