Individual and Opportunity Factors Influencing Job Creation in New Firms

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Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

Social media is increasingly being employed to develop Cultural Ecosystem Services (CES) indicators. The image-sharing platform Flickr has been one of the most popular sources of data. Most large-scale studies, however, tend to only use the number of image ...

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

Being able to work effectively in a team is a vital professional skill but how do students in different disciplines, engineering and hospitality, display their emotions when working together? We investigated their self-reported use of emotional labour stra ...

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI ...

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

The acquisition of survey responses is a crucial component in conducting research aimed at comprehending public opinion. However, survey data collection can be arduous, time-consuming, and expensive, with no assurance of an adequate response rate. In this ...

Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neural re ...

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...

What makes written text appealing? In this registered report, we study the linguistic characteristics of news headline success using a large-scale dataset of field experiments (A/B tests) conducted on the popular website comparing multiple headline variant ...

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents. In this setup, each agent receives data that might be generated from a different hypothesis (or state) than the data other agents receive. In c ...

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds directly on the specific Maximum Likelihood ratio treatment of uncertainties a ...

Decay heat calculations of spent nuclear fuel (SNF) using Polaris and ORIGEN codes in the SCALE code sys-tem, and CASMO5 code, are validated using measurements from the Clab and GE-Morris facilities. Multiple hypothesis testing, relying on permutations and ...

Social learning algorithms provide models for the formation of opinions over social networks resulting from local reasoning and peer-to-peer exchanges. Interactions occur over an underlying graph topology, which describes the flow of information among the ...

Characteristics of the spent nuclear fuel (SNF) are typically calculated, requiring validation a priori. The validation process relies on the difference between calculations and measurements, namely the bias. Usually, predicting the bias based on benchmark ...

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

A common assumption in the social learning literature is that agents exchange information in an unselfish manner. In this work, we consider the scenario where a subset of agents aims at driving the network beliefs to the wrong hypothesis. The adversaries a ...

Individual and Opportunity Factors Influencing Job Creation in New Firms

Chattez avec Graph Search

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

Understanding the sentiment associated with cultural ecosystem services using images and text from social media

Social Opinion Formation and Decision Making Under Communication Trends

“But of course i’m going to look happy” or “He needed to know I was angry”? Comparing use of emotional labour in teamwork in engineering and hospitality students

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Partial Information Sharing Over Social Learning Networks

Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

Learnable latent embeddings for joint behavioural and neural analysis

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Linguistic effects on news headline success: Evidence from thousands of online field experiments (Registered Report)

Social Learning with Disparate Hypotheses

Lightweight HI source finding for next generation radio surveys

A note on universal inference

Learning new physics from an imperfect machine

Validation of spent nuclear fuel decay heat calculations using Polaris, ORIGEN and CASMO5

Explainability and Graph Learning From Social Interactions

Data-Driven Predictive Models: Calculational Bias in Characterization of Spent Nuclear Fuel

Multiple testing with test statistics following heavy-tailed distributions

Social Learning Under Inferential Attacks