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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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48 results for quality of life

Study creates a global living index to assess quality of life.

problem Long-term impacts of global economic changes on living conditions.
method Machine learning framework combining socio-economic factors.
result Developed a practical tool for policymakers to identify areas needing improvement.

Method reconstructs hidden Markov chains from insurance data.

problem Recovering hidden Markov chains from incomplete insurance data.
method Neural architecture to explicitly provide transition probabilities.
result Neural model successfully validates decompression of insurance information.

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…

2015-10-16abs ↗pdf ↗

CDLF predicts product life-cycles in cold-start phases with high accuracy.

problem Forecasting new products in early phases when data is scarce.
method Conditional Diffusion Life-cycle Forecaster (CDLF) combining static descriptors, reference trajectories, and new observations.
result CDLF outperforms classical models in accuracy and probabilistic forecasting.

How are economic activities linked to geographic locations? To answer this question, we use a data-driven approach that builds on the information about location, ownership and economic activities of the world's 3,000 largest firms and their almost one million subsidiaries. From this information we generate a bipartite …

2015-12-09abs ↗pdf ↗

Optimizes treatment duration to maximize quality-adjusted lifetime.

problem Balancing risks and benefits in clinical decision making.
method Proposes a weighted estimating equation to adjust for confounding and informative censoring, and a nonparametric estimator for mean counterfactual quality-adjusted lifetime.
result Shows the optimal time for percutaneous endoscopic gastrostomy insertion in ALS patients.

Crowdsourcing and active learning reduce manual annotation in social media event classification.

problem Manual annotation is time-consuming and resource-intensive in social media event classification.
method Crowdsourcing pipeline combined with active learning strategies.
result Active learning strategies help reduce the number of tweets needed for classification.

EGFC learns from streaming data to classify power quality disturbances.

problem Real-time detection and classification of power quality disturbances.
method Evolving Gaussian Fuzzy Classification (EGFC) framework with semi-supervised learning.
result Encouraging classification results from online data streams.

One of the biggest challenges in the research of generative adversarial networks (GANs) is assessing the quality of generated samples and detecting various levels of mode collapse. In this work, we construct a novel measure of performance of a GAN by comparing geometrical properties of the underlying data manifold and …

2018-02-07abs ↗pdf ↗

We determine how an individual can use life insurance to meet a bequest goal. We assume that the individual's consumption is met by an income, such as a pension, life annuity, or Social Security. Then, we consider the wealth that the individual wants to devote towards heirs (separate from any wealth related to the afor…

2014-02-21abs ↗pdf ↗

The paper revisits and applies FTAP to life insurance and annuities pricing.

problem Non-arbitrage pricing of life contingent assets in dynamic markets.
method Revisit FTAP, use martingale theory, apply FTAP to life insurance and annuities, clarify assumptions.
result Valuation formula for life contingent assets including life insurance policies and annuities.

Develops a two-stage conformal prediction method for Parkinson's disease medication needs.

problem Heterogeneous disease progression and treatment response in Parkinson's Disease.
method Two-stage conformal prediction framework with statistical guarantees.
result Quantifies uncertainty in medication needs predictions, improving clinical trust and quality of life.

Improving the quality of end-of-life care for hospitalized patients is a priority for healthcare organizations. Studies have shown that physicians tend to over-estimate prognoses, which in combination with treatment inertia results in a mismatch between patients wishes and actual care at the end of life. We describe a …

2017-11-17abs ↗pdf ↗

The study examines how different interpolation methods affect the decomposition of life insurance surplus.

problem The impact of different interpolation methods on the decomposition of life insurance surplus.
method The study uses the IASU decomposition method to analyze the effects of different interpolation methods (Lee-Carter and linear) on the surplus decomposition.
result Lee-Carter and linear interpolation yield almost identical decompositions, while constant approximations result in different decompositions.

modAL is a modular active learning framework for Python, aimed to make active learning research and practice simpler. Its distinguishing features are (i) clear and modular object oriented design (ii) full compatibility with scikit-learn models and workflows. These features make fast prototyping and easy extensibility p…

2018-05-02abs ↗pdf ↗

Novel approach models life events using causal discovery and survival analysis.

problem Modeling life event choices and occurrence from a probabilistic perspective.
method Bi-level problem formulation: causal discovery for life events graph, survival analysis for time-to-event modeling.
result Identification of causal relationships and factors influencing transition rates between life events.

Bayesian MS-VAR model for pricing equity-linked life insurance products.

problem Pricing and hedging equity-linked life insurance products on maximum of several assets.
method Introduces Bayesian Markov-Switching Vector Autoregressive (MS-VAR) process to model economic variables and insured's lifetime.
result Obtains net single premiums and hedging formulas for equity-linked life insurance products.

Optimizes capital structure for life insurance companies with surplus participation.

problem Determining the optimal participation rate in life insurance contracts.
method Adapted Leland's dynamic capital structure model to life insurance context.
result Optimal participation rate is highly sensitive to contract duration and tax rate.

Investigates optimal life insurance and annuity decisions in inflationary economies.

problem Optimal consumption and investment decisions in an inflationary economy with money illusion.
method Formulated as a random horizon utility maximization problem, derived optimal strategy.
result Money illusion increases life insurance demand for young adults and reduces annuity demand for retirees.

The study analyzes river water quality using statistical and machine learning methods.

problem Analyzing spatio-temporal dynamics of dissolved oxygen in the River Thames.
method Superstatistical methods and machine learning (e.g., Light Gradient Boosting Machine, Informer model).
result The Informer model outperforms others in long-term dissolved oxygen concentration forecasting.

Continuous collection of physiological data from wearable sensors enables temporal characterization of individual behaviors. Understanding the relation between an individual's behavioral patterns and psychological states can help identify strategies to improve quality of life. One challenge in analyzing physiological d…

2019-11-16abs ↗pdf ↗

With the recent trend of applying machine learning in every aspect of human life, it is important to incorporate fairness into the core of the predictive algorithms. We address the problem of predicting the quality of public speeches while being fair with respect to sensitive attributes of the speakers, e.g. gender and…

2019-11-25abs ↗pdf ↗

This paper explores how machine learning can improve life insurance risk assessment.

problem Limited use of machine learning in life insurance due to statistical models' efficiency.
method Review and extension of traditional actuarial methodologies with machine learning techniques.
result Developed Python library for life insurance data, improving risk modeling.

LIFE framework improves model accuracy and interpretability.

problem Achieving high prediction accuracy and interpretability in neural networks.
method Three-step process: subset definition, feature creation, and linear model combination.
result LIFE consistently outperforms other models in prediction accuracy and interpretability.

Study finds consumers are more price-sensitive before livestreams than after.

problem Understanding consumer demand during livestreaming lifecycle.
method Examined consumer demand for live events and recorded versions using data from a livestreaming platform.
result Demand is more price-sensitive before livestreams than after.

Investigates timing and asset allocation for life insurance in uncertain financial planning.

problem Optimal timing and asset allocation for life insurance in uncertain financial planning.
method Analytical solutions using duality theory and free-boundary problems.
result Explicit expressions for value functions and optimal strategies in both scenarios.