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.
The paper analyzes fairness of compensation-based risk-sharing schemes for fund payouts.
New model maps malaria prevalence across Kenya's changing administrative boundaries.
Germany's tax admin costs likely exceed 20% of total revenue, requiring system improvement.
Research funding agencies routinely use a proportion of their total revenues to support internal administration and marketing costs. The ratio of administration to total costs, referred to as the administration ratio, is highly variable and within any single fund depends on many factors including the number and average…
This paper addresses issues with the Brier score in administrative censoring scenarios.
Machine learning methods have gained a great deal of popularity in recent years among public administration scholars and practitioners. These techniques open the door to the analysis of text, image and other types of data that allow us to test foundational theories of public administration and to develop new theories. …
Study improves risk evaluation timing with right-censored reporting delays.
Study on tax administration issues and their impact on Georgia's budget revenues.
New method simplifies data analysis.
Paper analyzes AI's impact on job tasks, predicting future demands.
This article was withdrawn by the arXiv.org administrators since it plagiarizes math.AT/0401211.
This article was withdrawn by the arXiv.org administrators since it plagiarizes math.GT/0011056.
A2A metric evaluates bias correction methods, reducing ATE estimation errors.
Deep learning improves CVD risk prediction from health records.
The past decade has seen an explosion in the amount of digital information stored in electronic health records (EHR). While primarily designed for archiving patient clinical information and administrative healthcare tasks, many researchers have found secondary use of these records for various clinical informatics tasks…
This paper has been withdrawn by arXiv administrators because of disputed claims of authorship among former collaborators
Policy shifts between Trump and Biden impact ESG investments, creating volatility.
This version withdrawn by arXiv administrators because the submitter did not have the right to agree to our license at the time of submission.
Interpretable neural networks improve economic research by balancing accuracy and transparency.
We demonstrate by mathematical analysis and systematic computer simulations that redistribution can lead to sustainable growth in a society. The human capital dynamics of each agent is described by a stochastic multiplicative process which, in the long run, leads to the destruction of individual human capital and the e…
Accurate prediction of suicide risk in mental health patients remains an open problem. Existing methods including clinician judgments have acceptable sensitivity, but yield many false positives. Exploiting administrative data has a great potential, but the data has high dimensionality and redundancies in the recording …
Study shows Lula's Zero Hunger program reduced income inequality in Brazil.
We present the Network-based Biased Tree Ensembles (NetBiTE) method for drug sensitivity prediction and drug sensitivity biomarker identification in cancer using a combination of prior knowledge and gene expression data. Our devised method consists of a biased tree ensemble that is built according to a probabilistic bi…
Equity-Directed Bootstrapping improves model performance across groups in imbalanced datasets.
Framework for fast CAT calibration and administration using AutoML and IRT.
Study uses data to analyze COPD patients' impact on hospital systems.
Most of the existing solutions to enterprise threat management are preventive approaches prescribing means to prevent policy violations with varying degrees of success. In this paper we consider the complementary scenario where a number of security violations have already occurred, or security threats, or vulnerabiliti…
Paper proposes a method to estimate confidence bands for survival random forests.
This study is motivated by the magnitude of the problem of Louisiana high school dropout and its negative impacts on individual and public well-being. Our goal is to predict students who are at risk of high school dropout, by examining Louisiana administrative dataset. Due to the imbalanced nature of the dataset, imbal…
LLMs can identify tax strategies, potentially revolutionizing tax enforcement.
QLSTM outperforms LSTM in predicting KSE 100 index movements.
Deep learning has recently demonstrated state-of-the art performance on key tasks related to the maintenance of computer systems, such as intrusion detection, denial of service attack detection, hardware and software system failures, and malware detection. In these contexts, model interpretability is vital for administ…
Modeling disease progression in healthcare administrative databases is complicated by the fact that patients are observed only at irregular intervals when they seek healthcare services. In a longitudinal cohort of 76,888 patients with chronic obstructive pulmonary disease (COPD), we used a continuous-time hidden Markov…
Method fuses low and high-resolution data for better health estimates.
DCEM algorithm reduces bias in machine learning models trained on selective labels.
The paper learns personalized treatment rules from observational data.
New DP mechanism SWAG-PPM improves privacy in deep learning models.
Study re-evaluates MIMIC-III codes, finding many are under-coded.
The study examines how alternative resource adequacy contract designs affect market participants' risk profiles and resource mix.
Risk prediction is central to both clinical medicine and public health. While many machine learning models have been developed to predict mortality, they are rarely applied in the clinical literature, where classification tasks typically rely on logistic regression. One reason for this is that existing machine learning…
In this paper, we consider the problem of predicting demographics of geographic units given geotagged Tweets that are composed within these units. Traditional survey methods that offer demographics estimates are usually limited in terms of geographic resolution, geographic boundaries, and time intervals. Thus, it would…
Paper uses 2-step Gradient Boosting to predict VAT tax gap.
The availability of a large amount of electronic health records (EHR) provides huge opportunities to improve health care service by mining these data. One important application is clinical endpoint prediction, which aims to predict whether a disease, a symptom or an abnormal lab test will happen in the future according…
This dataset contains the annual aggregated income taxes of all the Italian municipalities over the years 2007-2011. Data are clustered over the Italian regions and provinces. The source of the data is the Italian Ministry of Economics and Finance. The administrative variations in Italy over the quinquennium have been …
The biological processes involved in a drug's mechanisms of action are oftentimes dynamic, complex and difficult to discern. Time-course gene expression data is a rich source of information that can be used to unravel these complex processes, identify biomarkers of drug sensitivity and predict the response to a drug. H…
System automates identification of cancer drug repurposing from PubMed.
This paper explains tax policy for crypto assets in a rapidly evolving tech landscape.
This study simulates the evolution of artificial economies in order to understand the tax relevance of administrative boundaries in the quality of life of its citizens. The modeling involves the construction of a computational algorithm, which includes citizens, bounded into families; firms and governments; all of them…