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696
KSVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
, 2006
"... In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signalatoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and inc ..."
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Cited by 935 (41 self)
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by either selecting one from a prespecified set of linear transforms or adapting the dictionary to a set of training signals. Both of these techniques have been considered, but this topic is largely still open. In this paper we propose a novel algorithm for adapting dictionaries in order to achieve sparse
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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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
Automatic Extraction of Biological Information From Scientific Text: ProteinProtein Interactions
, 1999
"... We describe the basic design of a system for automatic detection of proteinprotein interactions extracted from scientific abstracts. By restricting the problem domain and imposing a number of strong assumptions which include prespecified protein names and a limited set of verbs that represent ac ..."
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Cited by 221 (5 self)
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We describe the basic design of a system for automatic detection of proteinprotein interactions extracted from scientific abstracts. By restricting the problem domain and imposing a number of strong assumptions which include prespecified protein names and a limited set of verbs that represent
Multitask evolutionary shaping without prespecified representations
 In Proceedings of the Genetic and Evolutionary Computation Conference
, 2010
"... Shaping functions can be used in multitask reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, researchers have prespecified a separate representation for shaping and value functions in multitask settings. However, no ..."
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Cited by 7 (4 self)
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Shaping functions can be used in multitask reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, researchers have prespecified a separate representation for shaping and value functions in multitask settings. However
Constrained Delaunay triangulations
 Algorithmica
, 1989
"... Given a set of n vertices in the plane together with a set of noncrossing edges, the constrained Delaunay triangulation (CDT) is the triangulation of the vertices with the following properties: (1) the prespecified edges are included in the triangulation, and (2) it is as close as possible to the De ..."
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Cited by 207 (4 self)
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Given a set of n vertices in the plane together with a set of noncrossing edges, the constrained Delaunay triangulation (CDT) is the triangulation of the vertices with the following properties: (1) the prespecified edges are included in the triangulation, and (2) it is as close as possible
Simultaneous embeddings with vertices mapping to prespecified points. In: Computing and Combinatorics
, 2012
"... Abstract. We discuss the problem of embedding graphs in the plane with restrictions on the vertex mapping. In particular, we introduce a technique for drawing planar graphs with a fixed vertex mapping that bounds the number of times edges bend. An immediate consequence of this technique is that any ..."
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Cited by 1 (1 self)
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embeddings of k uniformly random planar graphs with vertices mapping to a fixed, common point set. We explain how to achieve such a drawing so that edges map to piecewise linear curves with O(n1− 1 k) bends each, which holds with overwhelming probability. This result improves upon the previously best known
Microscopic Evolution of Social Networks
, 2008
"... We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic pr ..."
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Cited by 206 (10 self)
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local preferential attachment. Based on our observations, we develop a complete model of network evolution, where nodes arrive at a prespecified rate and select their lifetimes. Each node then independently initiates edges according to a “gap” process, selecting a destination for each edge according to a simple
Bayesian coalescent inference of past population dynamics from molecular sequences.
 Molecular Biology and Evolution,
, 2005
"... We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently sam ..."
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Cited by 203 (16 self)
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We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently
Adaptive clinical trial designs with prespecified rules for modifying the sample size: understanding efficient types of adaptation. Statistics in Medicine
, 2012
"... Methods allowing unplanned adaptations to the sample size based on the interim estimate of treatment effect do not base inference on the minimal sufficient statistic and suffer losses in efficiency when compared to group sequential designs [1, 2, 3]. However, when adaptive sampling plans are comple ..."
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Cited by 2 (1 self)
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are completely prespecified at the design stage of the trial, investigators can proceed with frequentist inference based on the minimal sufficient statistic at the analysis stage. In the context of two general settings where different optimality criteria govern the choice of clinical trial design, we quantify
A Method for approximately sampling highdimensional Count Variables with prespecified Pearson Correlation
"... We suggest an approximative method for sampling highdimensional count random variables with a specified Pearson correlation. As in the continuous case copulas can be used to construct multivariate discrete distributions. We utilize Gaussian copulas for the construction. A major task is to determine ..."
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Cited by 3 (2 self)
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distributions. We will illustrate that our sampling approach generates accurate results even in high dimensions in several settings with Poisson, generalized Poisson, zeroinflated generalized Poisson and Negative Binomial margins for a variety of marginal parameters and outperforms a widely used ’naive
Results 1  10
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696