Social Learning with Adaptive Models

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In the context of discrete choice modeling, the extraction of potential behavioral insights from large datasets is often limited by the poor scalability of maximum likelihood estimation. This paper proposes a simple and fast dataset-reduction method that i ...

This paper determines how to define a discretely implemented Fourier transform when analysing an observed spatial point process. To develop this transform we answer four questions; first what is the natural definition of a Fourier transform, and what are i ...

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-C-l estimates of tomographic cosmic shear power spectra. Using two existing publicly av ...

This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitud ...

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...

Traditional methods for Unsupervised Domain Adaptation (UDA) targeting semantic segmentation exploit information common to the source and target domains, using both labeled source data and unlabeled target data. In this paper, we investigate a setting wher ...

Optimal performance of civil infrastructure is an important aspect of liveable cities. A judicious combination of physics-based models with monitoring data in a validated methodology that accounts for uncertainties is explored in this paper. This methodolo ...

Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...

Biological oscillators are pervasive in biology, covering all aspects of life from enzyme kinetics reactions to population dynamics. Although their behaviour has been intensively studied in the last decades, the recent advances of high-throughput experimen ...

Point clouds have been gaining importance as a solution to the problem of efficient representation of 3D geometric and visual information. They are commonly represented by large amounts of data, and compression schemes are important for their manipulation ...

The typical enterprise data architecture consists of several actively updated data sources (e.g., NoSQL systems, data warehouses), and a central data lake such as HDFS, in which all the data is periodically loaded through ETL processes. To simplify query p ...

Using data collected with the Belle detector at the KEKB asymmetric-energy e(+)e(-) collider, we measure the energy dependence of the e(+)e(-) -> h(b)(nP)pi(+)pi(-) (n = 1, 2) cross sections from thresholds up to 11.02 GeV. We find clear gamma(10860) and g ...

Author Summary In recent years, considerable attention has been given to the evolution of drug resistance in the influenza A H1N1 strain. As a major annual cause of morbidity and mortality, combined with the rapid global spread of drug resistance, influenz ...

Social Learning with Adaptive Models

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Resampling estimation of discrete choice models

What is the Fourier Transform of a Spatial Point Process?

Euclid: Covariance of weak lensing pseudo-C-l estimates Calculation, comparison to simulations, and dependence on survey geometry

Experimental assessment of traffic density estimation at link and network level with sparse data

Is There a Cap on Longevity? A Statistical Review

SiML: Sieved Maximum Likelihood for Array Signal Processing

Uncertainty Reduction for Model Adaptation in Semantic Segmentation

Validating model-based data interpretation methods for quantification of reserve capacity

Deep Learning Approaches for Auditory Perception in Robotics

Inference methods for the study of interacting biological oscillators in single-cells

Point cloud subjective evaluation methodology based on reconstructed surfaces

No data left behind: real-time insights from a complex data ecosystem

Energy Scan of the e(+)e(-) -> h(b)(nP)pi(+)pi(-) (n=1, 2) Cross Sections and Evidence for gamma(11020) Decays into Charged Bottomoniumlike States

Influenza Virus Drug Resistance: A Time-Sampled Population Genetics Perspective