arXiv research

Two stochastic representations help prove infinite lifetime and bound gradients on sub-Riemannian manifolds.

A neural-network model clusters subjects based on their lifetime distributions.

Optimizes treatment duration to maximize quality-adjusted lifetime.

We provide investment advice for an individual who wishes to minimize her lifetime poverty, with a penalty for bankruptcy or ruin. We measure poverty via a non-negative, non-increasing function of (running) wealth. Thus, the lower wealth falls and the longer wealth stays low, the greater the penalty. This paper general…

Paper uses RNN to predict SaaS user lifetime value.

New features from early battery cycles predict lifetime with high accuracy.

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 …

Machine learning speeds up FLIM analysis in biomedical research.

optHSIC tests independence between covariates and censored lifetimes using optimal transport.

A new model for lifetime maximization with reneging in heterogeneous outcomes.

Predict player lifetime value based on engagement metrics.

Study uses Open Banking data to estimate customer value, showing potential 21% increase.

Deep neural networks outperform parametric models in predicting customer lifetime value in video games.

In this note, we explicitly solve the problem of maximizing utility of consumption (until the minimum of bankruptcy and the time of death) with a constraint on the probability of lifetime ruin, which can be interpreted as a risk measure on the whole path of the wealth process.

Paper tackles lifetime ruin with hedge funds and high-watermark fees, considering drift uncertainty.

We establish when the two problems of minimizing a function of lifetime minimum wealth and of maximizing utility of lifetime consumption result in the same optimal investment strategy on a given open interval $O$ in wealth space. To answer this question, we equate the two investment strategies and show that if the indi…

We study a risk sensitive control version of the lifetime ruin probability problem. We consider a sequence of investments problems in Black-Scholes market that includes a risky asset and a riskless asset. We present a differential game that governs the limit behavior. We solve it explicitly and use it in order to find …

We show that the mutual fund theorems of Merton (1971) extend to the problem of optimal investment to minimize the probability of lifetime ruin. We obtain two such theorems by considering a financial market both with and without a riskless asset for random consumption. The striking result is that we obtain two-fund the…

This report is concerned with the Mondrian process and its applications in machine learning. The Mondrian process is a guillotine-partition-valued stochastic process that possesses an elegant self-consistency property. The first part of the report uses simple concepts from applied probability to define the Mondrian pro…

ASOS uses embeddings to predict customer lifetime value.

Study the systemic risk of big banks through a unique common shock model.

Wireless sensor networks are composed of distributed sensors that can be used for signal detection or classification. The likelihood functions of the hypotheses are often not known in advance, and decision rules have to be learned via supervised learning. A specific such algorithm is Fisher discriminant analysis (FDA),…

The paper stabilizes PD term structures under forecast uncertainty using a Kalman filter with an anchored observation model.

The study improves CLV predictions in retail banking with machine learning.

We find the minimum probability of lifetime ruin of an investor who can invest in a market with a risky and a riskless asset and can purchase a deferred annuity. Although we let the admissible set of strategies of annuity purchasing process to be increasing adapted processes, we find that the individual will not buy a …

Paper proposes decentralized annuities for better retirement security.

Automates RL for LTV in recommender systems.

New approach models individual vitality for better mortality predictions.

We determine the optimal amount to invest in a Black-Scholes financial market for an individual who consumes at a rate equal to a constant proportion of her wealth and who wishes to minimize the expected time that her wealth spends in drawdown during her lifetime. Drawdown occurs when wealth is less than some fixed pro…

The study examines Cox models for lifetime loan default risk, addressing biased estimates by incorporating recurrent events.

We apply stochastic Perron's method to a singular control problem where an individual targets at a given consumption rate, invests in a risky financial market in which trading is subject to proportional transaction costs, and seeks to minimize her probability of lifetime ruin. Without relying on the dynamic programming…

Develops algorithms to optimize machine replacement schedules using operational data.

Greedy algorithm optimizes consumption habits with power utility.

Extends utility maximization theory for infinite horizons without strong no-arbitrage assumptions.

In general it is not clear which kind of information is supposed to be used for calculating the fair value of a contingent claim. Even if the information is specified, it is not guaranteed that the fair value is uniquely determined by the given information. A further problem is that asset prices are typically expressed…

The paper proves conditions for infinite lifetime of Brownian motion and regularity of heat flow.

CPDOs can't achieve a Cash-In event in finite tosses, mirroring Zeno's Paradox.

Proposes a method to predict RUL with domain adaptation for PHM.

Introduces TSI, a variance-based measure for persistence barcodes.

We assume that an individual invests in a financial market with one riskless and one risky asset, with the latter's price following geometric Brownian motion as in the Black-Scholes model. Under a constant rate of consumption, we find the optimal investment strategy for the individual who wishes to minimize the probabi…

In this paper, we prove a unique continuation or ``backwards-uniqueness'' theorem for solutions to the Ricci flow. A particular consequence is that the isometry group of a solution cannot expand within the lifetime of the solution.

Improved Mondrian Forests achieve optimal rate for online classification.

We determine the optimal robust investment strategy of an individual who targets at a given rate of consumption and seeks to minimize the probability of lifetime ruin when she does not have perfect confidence in the drift of the risky asset. Using stochastic control, we characterize the value function as the unique cla…

SAGA predicts multi-year earnings with adaptive intervals, improving forecast accuracy.

This research improves asset life prediction by integrating deep learning with mixture distributions.

URN neural network dynamically generates various neural structures during training.

We define an index of the fermionic signature operator on even-dimensional globally hyperbolic spin manifolds of finite lifetime. The invariance of the index under homotopies is studied. The definition is generalized to causal fermion systems with a chiral grading. We give examples of space-times and Dirac operators th…

Improves A/B testing for long-term outcomes in dynamic systems.