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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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2468 · Feb 202019922001200920172026
48 results for sponsor renewal

Optimizes ad pruning in sponsored search systems using reinforcement learning.

problem How to efficiently select top K ads from N candidates to maximize revenue.
method Model-free reinforcement learning approach considering downstream as a black-box environment.
result Remarkable improvements in revenue achieved through reinforcement learning.

Study on error probability for classification of heavy-tailed renewal processes.

problem Error probability in classification of heavy-tailed renewal processes.
method Asymptotic expressions for Bhattacharyya bound on misclassification error probabilities.
result Obtained asymptotic expressions for misclassification error probabilities.

This paper forecasts renewable energy prospects in South America through cross-border interconnection.

problem Lack of renewable energy integration across South American countries.
method Long-term scenario forecasting methodology applied to raw data from typical countries.
result Promoting cross-border interconnection towards renewables can optimize energy supply, reduce costs, and balance the energy matrix.

New methods resolve conflicting treatment effect estimates in health tech assessments.

problem Conflicting conclusions from different sponsors analyzing the same data.
method Arbitrated indirect treatment comparisons (ArMAIC) targeting a common target population.
result Estimates treatment effects in a common target population, resolving the MAIC paradox.

Proposes a pricing agent using reinforcement learning to balance renewable energy demand.

problem Intermittent renewable energy sources challenge carbon-free electricity generation.
method Reinforcement learning approach to balance customer demand with renewable energy generation.
result Demonstrates improved electricity pricing strategy for renewable energy integration.

Characterizes measures preserving compound mixed renewal process properties.

problem Preserving compound mixed renewal process properties under different probability measures.
method Characterization of progressively equivalent probability measures.
result Any compound mixed renewal process can be converted into a compound mixed Poisson process through a change of measures.

Paper develops framework for valuing and assessing credit risk in renewable PPAs.

problem Renewable PPAs expose both parties to counterparty credit risk.
method Modelled joint dynamics of electricity prices and renewable output, incorporated default probabilities.
result Provides transparent metric for PPA valuation under counterparty risk.

Machine learning models outperform traditional actuarial methods in predicting health insurance costs.

problem Improving accuracy in health insurance pricing to identify concession opportunities.
method Developed and evaluated two machine learning models at the patient and employer-group levels.
result Machine learning models outperformed traditional actuarial models by 20% in predicting costs.

Optimizes renewable energy mix to meet carbon-free targets at lowest cost.

problem Minimizing annual procurement costs while achieving specified carbon-free hourly performance.
method Probabilistic framework with simulation scenarios and probability constraints. Fixed set of renewable generators and load customer.
result Demonstrated that certain renewable energy portfolios can meet carbon-free targets at lower costs compared to others.

In this study we model the warranty claims process and evaluate the warranty servicing costs under non-renewing and renewing free repair warranties. We assume that the repair time for rectifying the claims is non-zero and the repair cost is a function of the length of the repair time. To accommodate the ageing of the p…

2018-03-02abs ↗pdf ↗

Modeling price formation in intraday electricity markets with renewable generation.

problem Price formation and optimal trading strategies in intraday electricity markets with intermittent renewable generation.
method Developed a tractable equilibrium model using stochastic control theory to identify optimal strategies and exhibit Nash equilibrium.
result Identified optimal trading strategies and exhibited Nash equilibrium in closed form for a finite number of agents and in the asymptotic framework of mean field games.

Federated learning calibrates insurance indices from renewable energy producers' data.

problem Calibrating parametric insurance indices under heterogeneous renewable energy production losses.
method Federated learning framework using Tweedie GLMs and distributed optimization.
result Federated learning recovers comparable index coefficients under moderate heterogeneity.

A new method uses Gaussian Processes to solve power flow problems with uncertain renewable and load inputs.

problem Solving power flow problems with uncertain renewable and load inputs.
method Non-parametric Bayesian inference-based uncertainty propagation using Gaussian Processes.
result The method provides reasonably accurate solutions with fewer samples and time compared to Monte-Carlo simulations.

Develops a method for probabilistic simulation of renewable energy production at grid scale.

problem Uncertainty in short-term electricity generation from renewable assets.
method Probabilistic framework with asset calibration, hierarchical clustering, and Gaussianization.
result Full uncertainty quantification at asset and collection levels.

The paper analyzes MENA region's energy consumption and policy needs for renewable energy.

problem High dependency on oil and low renewable energy penetration in MENA region.
method Analysis of World Bank datasets and policy portfolio in MENA countries.
result MENA region has high potential for solar energy but faces challenges in decoupling economic growth from energy consumption.

Calculation of an optimal tariff is a principal challenge for pricing actuaries. In this contribution we are concerned with the renewal insurance business discussing various mathematical aspects of calculation of an optimal renewal tariff. Our motivation comes from two important actuarial tasks, namely a) construction …

2016-05-19abs ↗pdf ↗

Ridge regression linked to Poisson resetting in statistical physics.

problem Understanding and extending ridge regularization in machine learning.
method Connecting stochastic resetting from statistical physics with ridge regularization in machine learning, using renewal processes.
result Exact filter identities for ridge regularization in various reset laws, including exponential and non-exponential.

Fossil power firms have recently profited more than renewables, but this may be a temporary phenomenon.

problem The profitability gap between renewable and fossil power firms in Europe.
method Machine-learning clustering and Bayesian model averaging.
result Renewable power firms are becoming more profitable, while fossil power firms are becoming less so.

We analyze the data of the Italian and U.S. futures on the stock markets and we test the validity of the Continuous Time Random Walk assumption for the survival probability of the returns time series via a renewal aging experiment. We also study the survival probability of returns sign and apply a coarse graining proce…

2006-06-06abs ↗pdf ↗

Paper studies second order tail probabilities in risk models.

problem Analyzing tail probabilities in risk models with constant interest force.
method Asymptotic expansion and weighted Kesten-type inequality for second order subexponential random variables.
result Second order asymptotic formulae for continuous-time renewal risk models are derived.

Power supply from renewable resources is on a global rise where it is forecasted that renewable generation will surpass other types of generation in a foreseeable future. Increased generation from renewable resources, mainly solar and wind, exposes the power grid to more vulnerabilities, conceivably due to their variab…

2017-06-27abs ↗pdf ↗

In this paper, we present an online reinforcement learning algorithm, called Renewal Monte Carlo (RMC), for infinite horizon Markov decision processes with a designated start state. RMC is a Monte Carlo algorithm and retains the advantages of Monte Carlo methods including low bias, simplicity, and ease of implementatio…

2018-04-03abs ↗pdf ↗

Predicting the click-through rate of an advertisement is a critical component of online advertising platforms. In sponsored search, the click-through rate estimates the probability that a displayed advertisement is clicked by a user after she submits a query to the search engine. Commercial search engines typically rel…

2017-07-07abs ↗pdf ↗

Examines climate financing for renewable energy projects using structured funds.

problem Valuation of structured climate financing on diverse renewable energy asset pools.
method Bottom-up Gaussian copula framework with LH++ model for diversification analysis.
result Shows how the mix of indirect and direct RE investments affects the sensitivity of the senior tranche.

New method controls renewable energy storage and portfolio selection with probabilistic constraints.

problem Control of McKean-Vlasov dynamics with probabilistic state constraints.
method Level-set approach for exact penalization and running maximum/integral cost.
result Extension to mean-field setting with machine learning algorithm.

Statistical depth metrics help identify risky power grid scenarios.

problem Identifying extreme scenarios for risk mitigation in power grid planning.
method Functional depth metrics for sub-selecting outlying scenarios.
result The proposed approach effectively identifies risky scenarios for operational risk mitigation.

This is the introduction and bibliography for lecture notes of a course given at the Summer School on Noncommutative Geometry and Applications, sponsored by the European Mathematical Society, at Monsaraz and Lisboa, Portugal, September 1-10, 1997. In the published version, an epilogue of recent developments and many ne…

1997-09-30abs ↗pdf ↗

Study shows targeting students with intermediate predicted outcomes is most effective for financial aid renewal.

problem Determining which students to target for financial aid renewal to maximize effectiveness.
method Used causal forest to estimate heterogeneous treatment effects and targeted students accordingly; compared targeting low vs high predicted probability outcomes.
result Targeting students with intermediate predicted outcomes yields the highest effectiveness in financial aid renewal.

MLM models match or exceed RN in generating wind power time series without location info.

problem Generating accurate long-term wind power time series without location information.
method Applied neural networks to MERRA2 wind speed data with and without location info.
result MLM models produce time series of equal or better quality than RN.

This paper discusses the financial risks faced by the UK Pension Protection Fund (PPF) and what, if anything, it can do about them. It draws lessons from the regulatory regimes under which other financial institutions, such as banks and insurance companies, operate and asks why pension funds are treated differently. It…

2011-03-30abs ↗pdf ↗