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.
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…
The paper analyzes fairness of compensation-based risk-sharing schemes for fund payouts.
New model maps malaria prevalence across Kenya's changing administrative boundaries.
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. …
Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within 30 days after a HF hospitalization is both a recognized indicator for disease progression and a source of considerable financial burden to the healthcare system. Consequently, the identification of patients at risk for …
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.
This article was withdrawn by the arXiv.org administrators since it plagiarizes math.AT/0401211.
This article was withdrawn by the arXiv.org administrators since it plagiarizes math.GT/0011056.
Deep learning improves CVD risk prediction from health records.
This paper has been withdrawn by arXiv administrators because of disputed claims of authorship among former collaborators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This version withdrawn by arXiv administrators because the submitter did not have the right to agree to our license at the time of submission.
New technique reduces FRTB IMA capital calculation burden by over 90%.
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.
Anomaly detection identifies unusual malaria transmission patterns in Ghana.
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.
Study predicts high school dropout risk in Louisiana using imbalanced learning techniques.
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.
Generative networks trained with sketching reduce computational burden.
The paper learns personalized treatment rules from observational data.
Optimal biomarker combinations for treatment-selection can be derived by minimizing total burden to the population caused by the targeted disease and its treatment. However, when multiple biomarkers are present, including all in the model can be expensive and hurt model performance. To remedy this, we consider feature …
Interpretable neural networks improve economic research by balancing accuracy and transparency.
The study examines how alternative resource adequacy contract designs affect market participants' risk profiles and resource mix.
The paper extracts structured data from physician-patient conversations, reducing clerical burden.
Paper uses 2-step Gradient Boosting to predict VAT tax gap.
Consequential decision-making typically incentivizes individuals to behave strategically, tailoring their behavior to the specifics of the decision rule. A long line of work has therefore sought to counteract strategic behavior by designing more conservative decision boundaries in an effort to increase robustness to th…
New model captures long-range patterns in sequences efficiently.
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…
A2A metric evaluates bias correction methods, reducing ATE estimation errors.
Novel algorithm reduces computational burden in IRL with finite-time guarantees.
FedMA improves federated learning for neural nets, matching and averaging model elements.
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…
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 article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is fou…