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9,636
Increasing Adder Efficiency by Exploiting Input Statistics
, 2007
"... Current techniques for characterizing the power consumption of adders rely on assuming that the inputs are completely random. However, the inputs generated by realistic applications are not random, and in fact include a great deal of structure. Input bits are more likely to remain in the same logic ..."
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Current techniques for characterizing the power consumption of adders rely on assuming that the inputs are completely random. However, the inputs generated by realistic applications are not random, and in fact include a great deal of structure. Input bits are more likely to remain in the same
Understanding Ocular Dominance Development From Binocular Input Statistics
"... It is hypothesized that the striate cortex is concerned with, among other things, removing binocular correlations in the inputs. This theory is applied to explain the different ocular dominance column (ODC) formations observed after visual developments under strabismus, excessive binocular correlati ..."
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Cited by 8 (1 self)
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correlations, normal environment, and monocular deprivation. These ODC formations are shown to be consequences of decorrelation coding strategies for different binocular input statistics. Experimental tests of the theory are suggested. 1 INTRODUCTION Recoding sensory inputs to remove the input redundancy has
2007 . Phaser crystallographic software
 658 – 674
"... Phaser is a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented in Phaser have been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms ..."
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Cited by 408 (1 self)
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Phaser is a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented in Phaser have been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new
A general framework for object detection
 Sixth International Conference on
, 1998
"... This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. By learning an object class in terms of ..."
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Cited by 395 (21 self)
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This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representation of an object class derived from a statistical analysis of the class instances. By learning an object class in terms
Automatically Generating Extraction Patterns from Untagged Text
 Department of Computer Science, Graduate School of Arts and Science, New York University
, 1996
"... Many corpusbased natural language processing systems rely on text corpora that have been manually annotated with syntactic or semantic tags. In particular, all previous dictionary construction systems for information extraction have used an annotated training corpus or some form of annotated input. ..."
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Cited by 373 (32 self)
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it with statistical techniques, we eliminated its dependency on tagged text. In experiments with the MUG4 terrorism domain, AutoSlogTS created a dictionary of extraction patterns that performed comparably to a dictionary created by AutoSlog, using only preclassified texts as input.
Open information extraction from the web
 IN IJCAI
, 2007
"... Traditionally, Information Extraction (IE) has focused on satisfying precise, narrow, prespecified requests from small homogeneous corpora (e.g., extract the location and time of seminars from a set of announcements). Shifting to a new domain requires the user to name the target relations and to ma ..."
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Cited by 373 (39 self)
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of relational tuples without requiring any human input. The paper also introduces TEXTRUNNER, a fully implemented, highly scalable OIE system where the tuples are assigned a probability and indexed to support efficient extraction and exploration via user queries. We report on experiments over a 9,000,000 Web
Dynamics of the Instantaneous Firing Rate in Response to Changes in Input Statistics
, 2004
"... Abstract. We review and extend recent results on the instantaneous firing rate dynamics of simplified models of spiking neurons in response to noisy current inputs. It has been shown recently that the response of the instantaneous firing rate to small amplitude oscillations in the mean inputs depend ..."
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Abstract. We review and extend recent results on the instantaneous firing rate dynamics of simplified models of spiking neurons in response to noisy current inputs. It has been shown recently that the response of the instantaneous firing rate to small amplitude oscillations in the mean inputs
Robust Anisotropic Diffusion
, 1998
"... Relations between anisotropic diffusion and robust statistics are described in this paper. Specifically, we show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edgestopping" function in the ani ..."
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Cited by 361 (17 self)
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Relations between anisotropic diffusion and robust statistics are described in this paper. Specifically, we show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edgestopping" function
Hamming weight of the NONADJACENTFORM UNDER VARIOUS INPUT STATISTICS
, 2007
"... The Hamming weight of the nonadjacent form is studied in relation to the Hamming weight of the standard binary expansion. In particular, we investigate the expected Hamming weight of the NAF of a ndigit binary expansion with k ones where k is either fixed or proportional to n. The expected Hammin ..."
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The Hamming weight of the nonadjacent form is studied in relation to the Hamming weight of the standard binary expansion. In particular, we investigate the expected Hamming weight of the NAF of a ndigit binary expansion with k ones where k is either fixed or proportional to n. The expected Hamming weight of NAFs of binary expansions with large ( ≥ n/2) Hamming weight is studied. Finally, the covariance of the Hamming weights of the binary expansion and the NAF is computed. Asymptotically, these Hamming weights become independent and normally distributed.
A framework for clustering evolving data streams. In:
 Proc of VLDB’03,
, 2003
"... Abstract The clustering problem is a difficult problem for the data stream domain. This is because the large volumes of data arriving in a stream renders most traditional algorithms too inefficient. In recent years, a few onepass clustering algorithms have been developed for the data stream proble ..."
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Cited by 359 (36 self)
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which uses only this summary statistics. The offline component is utilized by the analyst who can use a wide variety of inputs (such as time horizon or number of clusters) in order to provide a quick understanding of the broad clusters in the data stream. The problems of efficient choice, storage
Results 11  20
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9,636