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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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275380106 · Jun 202019922001200920172026
48 results for product age

The personal income distribution (PID) above the Pareto threshold is studied and modeled. A microeconomic model is proposed to simulate the PID and its evolution below and above the Pareto income threshold. The model balances processes of income production and dissipation for any person above 15 years of age. The model…

2008-11-03abs ↗pdf ↗

Tumblr, as a leading content provider and social media, attracts 371 million monthly visits, 280 million blogs and 53.3 million daily posts. The popularity of Tumblr provides great opportunities for advertisers to promote their products through sponsored posts. However, it is a challenging task to target specific demog…

2020-01-02abs ↗pdf ↗

We consider the role of unobservables, such as differences in search frictions, reservation wages, and productivities for the explanation of wage differentials between migrants and natives. We disentangle these by estimating an empirical general equilibrium search model with on-the-job search due to Bontemps, Robin, an…

2013-06-07abs ↗pdf ↗

Insurance and annuity products covering several lives require the modelling of the joint distribution of future lifetimes. In the interest of simplifying calculations, it is common in practice to assume that the future lifetimes among a group of people are independent. However, extensive research over the past decades …

2016-01-17abs ↗pdf ↗

Method converts age labels into distributions to improve speaker age estimation.

problem Label ambiguity in age labels makes precise speaker age estimation challenging.
method Converts age labels into label distributions and uses label distribution learning.
result Our method outperforms baseline methods by reducing MAE by 10% on a real-world dataset.

We solve a lifecycle model in which the consumer's chronological age does not move in lockstep with calendar time. Instead, biological age increases at a stochastic non-linear rate in time like a broken clock that might occasionally move backwards. In other words, biological age could actually decline. Our paper is ins…

2018-11-25abs ↗pdf ↗

The paper uses AI to analyze ECG data, revealing age-related changes and identifying key features.

problem Investigating age-related changes in ECG data to distinguish healthy from disease-related changes.
method Employed deep-learning and tree-based models on raw ECG signals and features from a diverse age group.
result Identified age-related declines in breathing rates and high SDANN values in elderly individuals.

Novel U-learning method for predicting continuous outcomes from high-dimensional data.

problem Challenges in making valid inferences on predictions from high-dimensional inputs.
method U-learning via combinatory multi-subsampling for ensemble predictions and confidence intervals.
result Valid inferences on predictions from Lasso and neural networks.

We introduce a new pension product that offers retirees the opportunity for a lifelong income and a bequest for their estate. Based on a tontine mechanism, the product divides pension savings between a tontine account and a bequest account. The tontine account is given up to a tontine pool upon death while the bequest …

2019-03-14abs ↗pdf ↗

A new FL algorithm reduces communication overhead by selectively updating model parameters.

problem Data heterogeneity and communication overhead in federated learning.
method Uses age of information metric to selectively update model parameters and group clients with similar data.
result Our method can expedite training and surpass other communication-efficient strategies in efficiency.

AGE improves graph embedding by smoothing features and iteratively enhancing node embeddings.

problem Challenges in attributed graph embedding, especially in preserving optimal low-pass characteristics and robustness.
method AGE, a novel framework combining Laplacian smoothing and adaptive encoding, addresses these issues.
result AGE consistently outperforms state-of-the-art methods on node clustering and link prediction tasks.

Study reveals that cryptocurrency price variations follow power-law distributions, influenced by age and market capitalization.

problem Understanding the statistical properties of cryptocurrencies, especially their price variations.
method Comprehensive investigation of over 7000 digital currencies, analyzing their price returns over time.
result Cryptocurrency price returns follow power-law distributions, with age and market capitalization influencing these distributions.

Machine learning models predict brain age with systematic bias, corrected in this study.

problem Systematic bias in machine learning regression models for brain age prediction.
method General constrained optimization approach to correct bias.
result Our method effectively eliminates the bias from brain age predictions.

Proposes a new model for mortality forecasting considering age groups and cohort effects.

problem Longevity risk due to ageing population.
method Mixed-effects time-series approach with age groups dependency and random cohort effects.
result Remarkable improvements in forecast accuracy compared to the CBD model.

Optimal annuitization strategy depends on age, labor income, and mortality risk.

problem Maximizing utility from consumption and labor income under age-dependent mortality.
method Dynamic programming approach to derive closed-form solutions.
result Post-retirement labor income acts as a substitute for annuitization.

This paper solves the problem of optimal dynamic consumption, investment, and healthcare spending with isoelastic utility, when natural mortality grows exponentially to reflect Gompertz' law and investment opportunities are constant. Healthcare slows the natural growth of mortality, indirectly increasing utility from c…

2019-01-02abs ↗pdf ↗

VNNs transfer well across datasets for brain age prediction using cortical thickness features.

problem Predicting brain age using anatomical features.
method Transferability of coVariance neural networks (VNNs) in brain age prediction.
result VNNs can assign anatomical interpretability to elevated brain age gap in AD.

This paper examines the optimal annuitization, investment and consumption strategies of a utility-maximizing retiree facing a stochastic time of death under a variety of institutional restrictions. We focus on the impact of aging on the optimal purchase of life annuities which form the basis of most Defined Benefit pen…

2015-06-19abs ↗pdf ↗

4-dim intrinsic (material) Riemannian metric GG of the material 4-D space-time continuum PP is utilized as the characteristic of the aging processes developing in the material. Manifested through variation of basic material characteristics such as density, moduli of elasticity, yield stress, strength, and toughness.,…

2006-04-16abs ↗pdf ↗

The paper uses distance correlation for brain connectivity and a novel multi-task learning model for age prediction.

problem Estimating age-related gender differences in brain functional connectivity.
method Estimates functional connectivity using distance correlation and proposes a non-convex multi-task learning model.
result The proposed non-convex multi-task learning model outperforms other models in age prediction and gender-specific connectivity.

In the age of data driven solution, the customer demographic attributes, such as gender and age, play a core role that may enable companies to enhance the offers of their services and target the right customer in the right time and place. In the marketing campaign, the companies want to target the real user of the GSM …

2019-02-20abs ↗pdf ↗

Modeling how individuals evolve over time is a fundamental problem in the natural and social sciences. However, existing datasets are often cross-sectional with each individual observed only once, making it impossible to apply traditional time-series methods. Motivated by the study of human aging, we present an interpr…

2018-07-12abs ↗pdf ↗

SPT predicts age and mass of red giants from spectra.

problem Challenges in age and mass estimation of red giants using traditional methods.
method SPT framework with Multi-head Hadamard Self-Attention and Mahalanobis distance-based loss function.
result Remarkable age and mass estimations with low errors and uncertainties.