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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.

168,742 papers · 148 categories

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15294458 · Jun 202019922001200920172026
48 results for Competing Technologies

Mathematical approach assesses human resource competences accurately.

problem Accurate assessment and representation of human resource competences.
method Detailed quantification scheme and mathematical approach.
result Flexible tools for optimal job assignment and recruitment.

Symmetry-electronic fingerprints reveal competing magnetic phases in two-dimensional materials.

problem Predicting magnetic ground states, moments, and anisotropy in two-dimensional magnets.
method Introduce the symmetry-electronic fingerprint (SEF), a physically interpretable representation that encodes crystallographic symmetry operations, Wyckoff-site geometry, and site-resolved electronic structure.
result SEF-trained models accurately classify magnetic ordering and regress moments alongside anisotropy energies.

Experts predict significant adoption of decentralized finance by 2034, with traditional finance adapting.

problem Adoption and integration of decentralized finance (DeFi) in financial services.
method Survey analysis using New Institutional Economics and Dynamic Capabilities Theory.
result Experts expect adoption of DeFi to rise from negligible to 43% by 2034, with traditional finance likely to embrace it.

Developing active inference agents for edge devices with limited resources.

problem Creating effective active inference agents on edge devices with limited computational resources.
method Introducing a software toolbox to accelerate the development of active inference agents by non-experts.
result Accelerates the democratization of active inference agents for edge devices.

Develops a deep learning framework to predict future tech directions for high-tech companies.

problem Difficult task in predicting future R&D trends for high-tech companies due to complexity and variety of factors.
method Deep Technology Forecasting (DTF) framework with three components: PCR, CTR, and DTT neural network.
result DTF framework precisely predicts future tech emphasis of companies using hybrid factors.

Paper improves competence estimation of machine learning models.

problem Estimating machine learning performance in real-world scenarios.
method ALICE Score: a pointwise competence estimator considering distributional, data, and model uncertainty.
result Significant improvements in competence prediction over state-of-the-art methods.

Study of dynamic competition between old and new technologies using a nonlinear map.

problem Dynamic competition between old and new technologies in market share.
method Simulations with three key parameters: scientific-technological, purely technological, and economic.
result Different outcomes in terms of technology prevalence based on interaction of key parameters.

The paper analyzes tech specialization and diversification at various scales.

problem Trade-offs between specialization and diversification in economic development.
method Patent data and Economic Complexity framework.
result Technological Coherence positively impacts growth at metropolitan areas but negatively at larger scales.

Dynamic Ensemble Selection (DES) techniques aim to select locally competent classifiers for the classification of each new test sample. Most DES techniques estimate the competence of classifiers using a given criterion over the region of competence of the test sample (its the nearest neighbors in the validation set). T…

2018-04-18abs ↗pdf ↗

Dynamic regressor selection (DRS) systems work by selecting the most competent regressors from an ensemble to estimate the target value of a given test pattern. This competence is usually quantified using the performance of the regressors in local regions of the feature space around the test pattern. However, choosing …

2019-04-09abs ↗pdf ↗

How technology affects growth or employment has long been debated. With a hiatus, the debate revived once again in the form of how Information and Communications Technology, as a form of new technology, exerts on productivity and employment. Information and Communications Technology perceived as General Purpose Technol…

2017-04-05abs ↗pdf ↗

Quantum crypto-economics models price risks in blockchain technology.

problem Quantum technology's potential to undermine blockchain security.
method Building financial models to price quantum risk in blockchain scenarios.
result Quantum crypto-economics models can assess and price quantum risks in blockchain.

Estimates yearly improvement rates for nearly all technologies using US patent data.

problem Providing a comprehensive account of technological change rates.
method Mapping patents to technology domains, calculating average centrality, and estimating improvement rates.
result Variation in improvement rates from 1.9% to 228.8% per year, with software-based domains often the fastest.

Paper reviews neurolinguistics and language technologies, emphasizing mutual enrichment.

problem Understanding brain activity during language processing.
method Brain imaging studies and natural language representations.
result Development of brain-aware natural language representations.

At the heart of technology transitions lie complex processes of social and industrial dynamics. The quantitative study of sustainability transitions requires modelling work, which necessitates a theory of technology substitution. Many, if not most, contemporary modelling approaches for future technology pathways overlo…

2013-04-12abs ↗pdf ↗

SurvivalBoost improves prediction of event times in competing risks scenarios.

problem Predicting event times in scenarios with multiple possible outcomes.
method Developed a strictly proper censoring-adjusted scoring rule for stochastic optimization of competing risks.
result SurvivalBoost outperforms 12 state-of-the-art models across various metrics.

Survival analysis in the presence of multiple possible adverse events, i.e., competing risks, is a pervasive problem in many industries (healthcare, finance, etc.). Since only one event is typically observed, the incidence of an event of interest is often obscured by other related competing events. This nonidentifiabil…

2018-07-16abs ↗pdf ↗

We introduce a quantitative approach to comparative statics that allows to bound the maximum effect of an exogenous parameter change on a system's equilibrium. The motivation for this approach is a well known paradox in multimarket Cournot competition, where a positive price shock on a monopoly market may actually redu…

2013-07-22abs ↗pdf ↗

Competency questions help experts select best clustering for energy data.

problem Ad hoc and subjective selection of clustering structures by domain experts.
method Formalize expert knowledge and requirements with competency questions.
result Competency questions improve reproducibility and evaluation of clustering applications.

This paper uses neural networks to accurately model competing risks in survival analysis.

problem Ignoring competing risks leads to biased survival estimation in machine learning models.
method The paper introduces constrained monotonic neural networks to model each competing survival distribution.
result The method ensures exact likelihood maximization with reduced computational cost.

Study examines HTE estimation from time-to-event data with competing events.

problem Estimating HTEs from time-to-event data with competing events.
method Outcome modeling approach using plug-in estimators for potential outcomes.
result Competing events introduce new challenges for HTE estimation.

HACSurv models dependencies between competing risks and censoring for improved survival analysis.

problem Inaccurate survival predictions due to ignoring dependencies between competing risks and censoring.
method HACSurv uses hierarchical Archimedean copulas to model dependencies and cause-specific survival functions.
result HACSurv improves accuracy in survival predictions and captures complex risk interactions.

PyDTS analyzes survival data with discrete intervals and competing risks.

problem Discrete-time survival analysis with competing risks and optional penalization.
method Regularized estimation methods, model evaluation metrics, variable screening tools, and simulation module.
result Supports research and development in discrete-time survival analysis.

This paper analyzes the dynamic incentives for technology adoption under a transferable permits system, which allows for strategic trading on the permit market. Initially, firms can invest both in low-emitting production technologies and trade permits. In the model, technology adoption and allowance price are generated…

2011-03-15abs ↗pdf ↗

Modeling tech transfer to explain convergence in Central and Eastern Europe.

problem Understanding mechanisms of technological diffusion in developing economies.
method Introducing a herding-based mechanism to model technological adoption and productivity growth.
result Explicit analytical solution showing nonlinear convergence to a moving frontier.

Geoeconomic analysis of venture capital portfolios reveals key emerging tech domains and countries.

problem Quantifying geoeconomic power and technological sovereignty through venture capital data.
method Economic complexity methods applied to venture capital portfolios and RVA metrics.
result Cloud Computing, Cybersecurity Tools, and Medtech have the highest concentration of specialization among high-GCI countries.

New method for discrete-time survival analysis with competing risks.

problem Discrete failure time data in survival analysis.
method Proposes a new estimation procedure for discrete-time survival analysis with competing events.
result Offers advantages over existing procedures and integrates regularized regression methods.

Prediction problems often admit competing models that perform almost equally well. This effect challenges key assumptions in machine learning when competing models assign conflicting predictions. In this paper, we define predictive multiplicity as the ability of a prediction problem to admit competing models with confl…

2019-09-14abs ↗pdf ↗

Specialists tolerate defects to gain flexibility, which can be removed when needed.

problem The economic benefits and limitations of deliberately tolerating defects in decision-making.
method Analyzes the conditions under which defects can be kept and removed, using economic models and structural analysis.
result A defect is profitably removable if certain conditions are met, and the premium is the support function of the class's ROC set.