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170,947
LONG-TERM OBJECTIVES
"... The long-term objective of this proposal is to develop methods for rapid assessment of seabed variability combined with detailed localized geoacoustic inversions to characterize the bottom for a given shallow-water environment. Consideration will be given to spatial and temporal variability in the w ..."
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The long-term objective of this proposal is to develop methods for rapid assessment of seabed variability combined with detailed localized geoacoustic inversions to characterize the bottom for a given shallow-water environment. Consideration will be given to spatial and temporal variability
A (2008): “Long-term objectives for government debt
"... Governments use national debt and the budget deficit as measures of fiscal position. But what should government policy aim to achieve with respect to these measures? Are these the right summary measures at which to be looking? This paper considers what the government should use as its fiscal targets ..."
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Cited by 5 (0 self)
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targets to achieve policies that are consistent with long-term fiscal objectives. Among its findings are: 1. Setting long-term targets for fiscal policy should start with a specification of fundamental policy objectives. There are at least three important long-term objectives associated with concerns
Long Term Object Drift Forecast in the Ocean With Tide and
, 2005
"... In this paper, we propose a new method to forecast the drift of objects in near coastal ocean on a period of several weeks. The proposed approach consists in estimating the probability of events linked to the drift using Monte Carlo simulations. It couples an averaging method which permits to decrea ..."
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Cited by 8 (4 self)
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In this paper, we propose a new method to forecast the drift of objects in near coastal ocean on a period of several weeks. The proposed approach consists in estimating the probability of events linked to the drift using Monte Carlo simulations. It couples an averaging method which permits
Not for Quotation Long-Term Objectives for Government Debt
, 2008
"... grateful to Bill Gale and Kent Smetters for comments on an earlier draft. ..."
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grateful to Bill Gale and Kent Smetters for comments on an earlier draft.
Spatial Memory and Long-Term Object Recognition Are Impaired by Circadian Arrhythmia and Restored by the
"... Performance on many memory tests varies across the day and is severely impaired by disruptions in circadian timing. We developed a noninvasive method to permanently eliminate circadian rhythms in Siberian hamsters (Phodopussungorus) so that we could investigate the contribution of the circadian syst ..."
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. These arrhythmic animals have deficits in spatial working memory and in long-term object recognition memory. In a T-maze, rhythmic control hamsters exhibited spontaneous alternation behavior late in the day and at night, but made random arm choices early in the day. By contrast, arrhythmic animals made only random
Effects of Long-Term Object Familiarity on Event-Related Potentials in the Monkey
, 2006
"... Although some change in the neural representation of an object must occur as it becomes familiar, the nature of this change is not fully understood. In humans, it has been shown that the N170—an evoked visual potential—is enhanced for classes of objects for which people have visual expertise. In thi ..."
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Cited by 7 (1 self)
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. In this study, we explored whether monkeys show a similar modulation in event-related potential (ERP) amplitude as a result of long-term familiarity by recording ERPs with chronically implanted electrodes over extended training periods spanning many sessions. In each of 3 experiments, we found larger amplitude
Market Efficiency, Long-Term Returns, and Behavioral Finance
, 1998
"... Market efficiency survives the challenge from the literature on long-term return anomalies. Consistent with the market efficiency hypothesis that the anomalies are chance results, apparent overreaction to information is about as common as underreaction, and post-event continuation of pre-event abnor ..."
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Cited by 787 (6 self)
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Market efficiency survives the challenge from the literature on long-term return anomalies. Consistent with the market efficiency hypothesis that the anomalies are chance results, apparent overreaction to information is about as common as underreaction, and post-event continuation of pre
Long Short-term Memory
, 1995
"... "Recurrent backprop" for learning to store information over extended time intervals takes too long. The main reason is insufficient, decaying error back flow. We briefly review Hochreiter's 1991 analysis of this problem. Then we overcome it by introducing a novel, efficient method c ..."
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Cited by 454 (58 self)
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called "Long Short Term Memory" (LSTM). LSTM can learn to bridge minimal time lags in excess of 1000 time steps by enforcing constant error flow through internal states of special units. Multiplicative gate units learn to open and close access to constant error flow. LSTM's update
Object Detection with Discriminatively Trained Part Based Models
"... We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their ..."
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Cited by 1422 (49 self)
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We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular
Distortion invariant object recognition in the dynamic link architecture
- IEEE TRANSACTIONS ON COMPUTERS
, 1993
"... We present an object recognition system based on the Dynamic Link Architecture, which is an extension to classical Artificial Neural Networks. The Dynamic Link Architecture ex-ploits correlations in the fine-scale temporal structure of cellular signals in order to group neurons dynamically into hig ..."
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Cited by 637 (80 self)
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are represented by sparse graphs, whose vertices are labeled by a multi-resolution description in terms of a local power spectrum, and whose edges are labeled by geometrical distance vectors. Object recognition can be formulated as elastic graph matching, which is performed here by stochastic optimization of a
Results 1 - 10
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170,947
