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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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0111 · May 201019922001200920172026
19 results for immigration

This paper focuses on a class of linear Hawkes processes with general immigrants. These are counting processes with shot noise intensity, including self-excited and externally excited patterns. For such processes, we introduce the concept of age pyramid which evolves according to immigration and births. The virtue if t…

2015-04-24abs ↗pdf ↗

Automates U.S. visa petition document classification and RFE response generation.

problem Manual effort in organizing visa petition documents and responding to RFEs.
method Ensemble of image and text classifiers for document categorization and text classifier for RFE evidence identification.
result Achieves considerable accuracy in automated responses while reducing processing time.

We compute exact values respectively bounds of "distances" - in the sense of (transforms of) power divergences and relative entropy - between two discrete-time Galton-Watson branching processes with immigration GWI for which the offspring as well as the immigration is arbitrarily Poisson-distributed (leading to arbitra…

2010-05-20abs ↗pdf ↗

Method selects valid IVs from a large set using clustering and test of overidentifying restrictions.

problem Selecting valid instrumental variables from a large set of candidates.
method Agglomerative hierarchical clustering combined with a test of overidentifying restrictions.
result Achieves oracle properties when the largest group of IVs is valid.

First we provide a simple set of sufficient conditions for the weak convergence of scaled affine processes with state space R+×RdR_+ \times R^d. We specialize our result to one-dimensional continuous state branching processes with immigration. As an application, we study the asymptotic behavior of least squares estimators…

2012-10-05abs ↗pdf ↗

The Hawkes process is a simple point process, whose intensity function depends on the entire past history and is self-exciting and has the clustering property. The Hawkes process is in general non-Markovian. The linear Hawkes process has immigration-birth representation. Based on that, Fierro et al. recently introduced…

2014-03-05abs ↗pdf ↗

New method identifies causal structure in count data using cumulants and path analysis.

problem Challenges in discovering causal structure from count data, especially due to non-identifiability.
method Poisson Branching Structural Causal Model (PB-SCM) with path analysis using high-order cumulants.
result Causal order is identifiable under specific conditions in PB-SCM using cumulant information.

Proposes a new machine learning-based method for conjoint analysis.

problem Testing the importance of factors in conjoint analysis with interactions.
method Conditional randomization test based on machine learning algorithms.
result Validates the importance of factors in conjoint analysis without model specification.

We propose and investigate two model classes for forward power price dynamics, based on continuous branching processes with immigration, and on Hawkes processes with exponential kernel, respectively. The models proposed exhibit jumps clustering features. Models of this kind have been already proposed for the spot price…

2019-10-29abs ↗pdf ↗

Most real-world document collections involve various types of metadata, such as author, source, and date, and yet the most commonly-used approaches to modeling text corpora ignore this information. While specialized models have been developed for particular applications, few are widely used in practice, as customizatio…

2017-05-25abs ↗pdf ↗

We develop a modelling framework for multiple yield curves driven by continuous-state branching processes with immigration (CBI processes). Exploiting the self-exciting behavior of CBI jump processes, this approach can reproduce the relevant empirical features of spreads between different interbank rates. In particular…

2019-11-07abs ↗pdf ↗

New text as data techniques offer a great promise: the ability to inductively discover measures that are useful for testing social science theories of interest from large collections of text. We introduce a conceptual framework for making causal inferences with discovered measures as a treatment or outcome. Our framewo…

2018-02-06abs ↗pdf ↗

Study uses ML to predict non-participation in ELSA COVID-19 follow-up studies.

problem Predicting non-participation in follow-up surveys due to various factors.
method Used machine learning algorithms including KNN, RF, AdaBoost, logistic regression, NN, and SVC.
result Random Forest (RF) outperforms other models in balanced accuracy.

Ensuring the security of transactions is currently one of the major challenges that banking systems deal with. The usage of face for biometric authentication of users is attracting large investments from banks worldwide due to its convenience and acceptability by people, especially in cross-domain scenarios, in which f…

2018-06-20abs ↗pdf ↗