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.
Hidden Markov Models analyze mobile health data to identify APNS states.
Method for understanding heterogeneous treatment effects in complex causal graphs.
Machine learning predicts trauma patient mortality risk.
PNNs improve treatment outcomes in TAVR and liver trauma.
New method evaluates personalized treatment in critical care, robust to death.
High-frequency trading models fail due to overfitting and survivor bias.
The paper explores how to fairly share longevity risk among participants of tontine schemes.
Study shows survivorship bias inflates returns in India's small-cap index.
In recent times, machine learning (ML) and artificial intelligence (AI) based systems have evolved and scaled across different industries such as finance, retail, insurance, energy utilities, etc. Among other things, they have been used to predict patterns of customer behavior, to generate pricing models, and to predic…
Driver drowsiness increases crash risk, leading to substantial road trauma each year. Drowsiness detection methods have received considerable attention, but few studies have investigated the implementation of a detection approach on a mobile phone. Phone applications reduce the need for specialised hardware and hence, …
We quantify the benefit of collectivised investment funds, in which the assets of members who die are shared among the survivors. For our model, with realistic parameter choices, an annuity or individual fund requires approximately 20\% more initial capital to provide as good an outcome as a collectivised investment fu…
Tontines were once a popular type of mortality-linked investment pool. They promised enormous rewards to the last survivors at the expense of those died early. And, while this design appealed to the gambling instinc}, it is a suboptimal way to generate retirement income. Indeed, actuarially-fair life annuities making c…
Human trafficking is among the most challenging law enforcement problems which demands persistent fight against from all over the globe. In this study, we leverage readily available data from the website "Backpage"-- used for classified advertisement-- to discern potential patterns of human trafficking activities which…
In a collectivised pension fund, investors agree that any money remaining in the fund when they die can be shared among the survivors. We give a numerical algorithm to compute the optimal investment-consumption strategy for an infinite collective of identical investors with exponential Kihlstrom--Mirman preferences, in…
Model captures asymmetric extreme events in financial returns.
Neural networks are known to be vulnerable to adversarial examples. Carefully chosen perturbations to real images, while imperceptible to humans, induce misclassification and threaten the reliability of deep learning systems in the wild. To guard against adversarial examples, we take inspiration from game theory and ca…
In this work, we developed a network inference method from incomplete data ("PathInf") , as massive and non-uniformly distributed missing values is a common challenge in practical problems. PathInf is a two-stages inference model. In the first stage, it applies a data summarization model based on maximum likelihood to …
New method for Bayesian inference on large datasets.
Upper bounds on utility for managing heterogeneous collectivised funds.
In a collectivised pension fund, investors agree that any money remaining in the fund when they die can be shared among the survivors. We compute analytically the optimal investment-consumption strategy for a fund of identical investors with homogeneous Epstein--Zin preferences, investing in the Black--Scholes mark…
Radio tomographic imaging (RTI) is an emerging technology for localization of physical objects in a geographical area covered by wireless networks. With attenuation measurements collected at spatially distributed sensors, RTI capitalizes on spatial loss fields (SLFs) measuring the absorption of radio frequency waves at…
Proposes a new model for testing causal structural priors and synthesizing data.
Study identifies and estimates treatment effect heterogeneity within principal stratification subpopulations.
Missing values challenge data analysis because many supervised and unsupervised learning methods cannot be applied directly to incomplete data. Matrix completion based on low-rank assumptions are very powerful solution for dealing with missing values. However, existing methods do not consider the case of informative mi…
Many in-hospital mortality risk prediction scores dichotomize predictive variables to simplify the score calculation. However, hard thresholding in these additive stepwise scores of the form "add x points if variable v is above/below threshold t" may lead to critical failures. In this paper, we seek to develop risk pre…
Over 150,000 new people in the United States are diagnosed with colorectal cancer each year. Nearly a third die from it (American Cancer Society). The only approved noninvasive diagnosis tools currently involve fecal blood count tests (FOBTs) or stool DNA tests. Fecal blood count tests take only five minutes and are av…
New algorithms allow multiple robots to search efficiently without central coordination.
A new tontine design aims to protect longevity risk with non-indexed investments.
Improved fMRI activation detection for single-subject studies.
Historical tontines promised enormous rewards to the last survivors at the expense of those who died early. While this design appealed to the gambling instinct, it is a suboptimal way to manage longevity risk during retirement. This is why fair life annuities making constant payments -- where the insurance company is e…
A ML-based method reconstructs 3D organ doses from 2D radiographs for pediatric abdominal radiotherapy.