Results 1  10
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14,717
Fitting a mixture model by expectation maximization to discover motifs in biopolymers.
 Proc Int Conf Intell Syst Mol Biol
, 1994
"... Abstract The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expect~tiou ma.,dmization to fit a twocomponent finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to th ..."
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Cited by 947 (5 self)
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to the data, probabilistically erasing tile occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which
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 (16 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
Optimal Aggregation Algorithms for Middleware
 IN PODS
, 2001
"... Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade under ..."
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Cited by 717 (4 self)
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simple algorithm (“the threshold algorithm”, or TA) that is optimal in a much stronger sense than FA. We show that TA is essentially optimal, not just for some monotone aggregation functions, but for all of them, and not just in a highprobability worstcase sense, but over every database. Unlike FA
Random Early Detection Gateways for Congestion Avoidance.
 IEEELACM Transactions on Networking,
, 1993
"... AbstractThis paper presents Random Early Detection (RED) gateways for congestion avoidance in packetswitched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving at the gatewa ..."
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Cited by 2716 (31 self)
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at the gateway or by setting a bit in packet headers. When the average queue size exceeds a preset threshold, the gateway drops or marks each arriving packet with a certain probability, where the exact probability is a function of the average queue size. RED gateways keep the average queue size low while
The Case for a SingleChip Multiprocessor
 IEEE Computer
, 1996
"... Advances in IC processing allow for more microprocessor design options. The increasing gate density and cost of wires in advanced integrated circuit technologies require that we look for new ways to use their capabilities effectively. This paper shows that in advanced technologies it is possible to ..."
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Cited by 440 (6 self)
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Advances in IC processing allow for more microprocessor design options. The increasing gate density and cost of wires in advanced integrated circuit technologies require that we look for new ways to use their capabilities effectively. This paper shows that in advanced technologies it is possible
Iterative hard thresholding for compressed sensing
 Appl. Comp. Harm. Anal
"... Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding algorithm when applied to the compressed sensing recovery probl ..."
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Cited by 329 (18 self)
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Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding algorithm when applied to the compressed sensing recovery
CE: Basic principles of ROC analysis
 Seminars in Nuclear Medicine
, 1978
"... The l imitations of diagnostic "accuracy " as a measure of decision performance require introduction of the concepts of the "sensit iv ity " and "specif ic i ty " of a diagnostic test, These measures and the related indices, "true positive fraction " and &quo ..."
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Cited by 376 (0 self)
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The l imitations of diagnostic "accuracy " as a measure of decision performance require introduction of the concepts of the "sensit iv ity " and "specif ic i ty " of a diagnostic test, These measures and the related indices, "true positive fraction "
Elementary Gates for Quantum Computation
, 1995
"... We show that a set of gates that consists of all onebit quantum gates (U(2)) and the twobit exclusiveor gate (that maps Boolean values (x, y)to(x, x⊕y)) is universal in the sense that all unitary operations on arbitrarily many bits n (U(2 n)) can be expressed as compositions of these gates. We in ..."
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Cited by 280 (11 self)
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investigate the number of the above gates required to implement other gates, such as generalized DeutschToffoli gates, that apply a specific U(2) transformation to one input bit if and only if the logical AND of all remaining input bits is satisfied. These gates play a central role in many proposed
New Directions in Traffic Measurement and Accounting
, 2001
"... Accurate network traffic measurement is required for accounting, bandwidth provisioning, and detecting DOS attacks. However, keeping a counter to measure the traffic sent by each of a million concurrent flows is too expensive (using SRAM) or slow (using DRAM). The current stateoftheart (e.g., Cis ..."
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Cited by 353 (11 self)
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Accurate network traffic measurement is required for accounting, bandwidth provisioning, and detecting DOS attacks. However, keeping a counter to measure the traffic sent by each of a million concurrent flows is too expensive (using SRAM) or slow (using DRAM). The current stateoftheart (e
Cryptographic Limitations on Learning Boolean Formulae and Finite Automata
 PROCEEDINGS OF THE TWENTYFIRST ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING
, 1989
"... In this paper we prove the intractability of learning several classes of Boolean functions in the distributionfree model (also called the Probably Approximately Correct or PAC model) of learning from examples. These results are representation independent, in that they hold regardless of the syntact ..."
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Cited by 347 (14 self)
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depth threshold circuits would have dramatic consequences for cryptography and number theory: in particular, such an algorithm could be used to break the RSA cryptosystem, factor Blum integers (composite numbers equivalent to 3 modulo 4), and detect quadratic residues. The results hold even if the learning
Results 1  10
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14,717