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.
Ebay uses forecasting and simulation to decide when to disable a vendor.
Improved disability insurance model with collective health claims.
New model for disability insurance reserving handles delays in claim information.
The International Classification of Functioning, Disability, and Health for Children and Youth (ICF-CY) is a scaffold for designating and systematizing data on functioning and disability. It offers a standard semantic and a theoretical foundation for the demarcation and extent of wellbeing and infirmity. The multidimen…
We consider a large, homogeneous portfolio of life or disability annuity policies. The policies are assumed to be independent conditional on an external stochastic process representing the economic-demographic environment. Using a conditional law of large numbers, we establish the connection between claims reserving an…
New model for insurance states using Markov jump processes with non-countable state space.
A Longitudinal Attribute-Conditioned Neural Network (LANTERN) framework for modeling health-state transition probabilities in irregular longitudinal data.
AI predicts dyslexia and dysgraphia in children.
Variational inference is a general approach for approximating complex density functions, such as those arising in latent variable models, popular in machine learning. It has been applied to approximate the maximum likelihood estimator and to carry out Bayesian inference, however, quantification of uncertainty with vari…
This paper describes and evaluates the use of Generative Adversarial Networks (GANs) for path planning in support of smart mobility applications such as indoor and outdoor navigation applications, individualized wayfinding for people with disabilities (e.g., vision impairments, physical disabilities, etc.), path planni…
SafeAccess identifies people in smart homes for safer access.
The aim of this paper is to propose an operational two-dimensional parametric adjustment for laws of maintenance in disability. The method suggested rests on splines in dimension 2; it is applied to a real data set, and the scale of reserving which results from it is compared with the scale of reference of the BCAC.
The paper proposes a new method for comparing logistic regression models across different populations.
We propose definitions of fairness in machine learning and artificial intelligence systems that are informed by the framework of intersectionality, a critical lens arising from the Humanities literature which analyzes how interlocking systems of power and oppression affect individuals along overlapping dimensions inclu…
Recurrent major mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilisation is an important clinical goal. Recent technological advances allow the prospective reporting of mood in real time enabl…
The P300 Brain-Computer Interface (BCI) is a well-established communication channel for severely disabled people. The P300 event-related potential is mostly characterized by its amplitude or its area, which correlate with the spelling accuracy of the P300 speller. Here, we introduce a novel approach for estimating the …
New concept of illiquidity linked to credit risk, using Jarrow & Turnbull's analogy.
Intersectionality is a framework that analyzes how interlocking systems of power and oppression affect individuals along overlapping dimensions including race, gender, sexual orientation, class, and disability. Intersectionality theory therefore implies it is important that fairness in artificial intelligence systems b…
Preterm births occur at an alarming rate of 10-15%. Preemies have a higher risk of infant mortality, developmental retardation and long-term disabilities. Predicting preterm birth is difficult, even for the most experienced clinicians. The most well-designed clinical study thus far reaches a modest sensitivity of 18.2-…
A major hurdle to clinical translation of brain-machine interfaces (BMIs) is that current decoders, which are trained from a small quantity of recent data, become ineffective when neural recording conditions subsequently change. We tested whether a decoder could be made more robust to future neural variability by train…
We propose Rademacher complexity bounds for multiclass classifiers trained with a two-step semi-supervised model. In the first step, the algorithm partitions the partially labeled data and then identifies dense clusters containing predominant classes using the labeled training examples such that the proportion of t…
The paper analyzes multivariate payments in multi-state life insurance using Markovian state processes.
BERT's success is due to limited attention patterns across heads, leading to overparametrization.
Systematic discriminatory biases present in our society influence the way data is collected and stored, the way variables are defined, and the way scientific findings are put into practice as policy. Automated decision procedures and learning algorithms applied to such data may serve to perpetuate existing injustice or…
Study uses NLP to analyze emotions and challenges of young people with IDD.
Gradient amplification boosts deep learning model performance without increasing training time.
Accurate classification of self-care problems in children who suffer from physical and motor affliction is an important problem in the healthcare industry. This is a difficult and a time consumming process and it needs the expertise of occupational therapists. In recent years, healthcare professionals have opened up to…
Study proposes a new GAN for realistic discrete financial orders.
New models for insurance claims accounting for delays.
This survey outlines methods to ensure fairness in machine learning.
Proposes a new method to prevent overfitting in deep neural networks.
New approach to counterfactual reasoning avoids demographic interventions.
Deep learning system classifies phonological categories from EEG data.
Perinatal stroke (PS) is a serious condition that, if undetected and thus untreated, often leads to life-long disability, in particular Cerebral Palsy (CP). In clinical settings, Prechtl's General Movement Assessment (GMA) can be used to classify infant movements using a Gestalt approach, identifying infants at high ri…
Automatic voice-controlled systems have changed the way humans interact with a computer. Voice or speech recognition systems allow a user to make a hands-free request to the computer, which in turn processes the request and serves the user with appropriate responses. After years of research and developments in machine …
The paper develops a valuation framework for GLWB-LTC contracts with Levy dynamics and stochastic interest rates.
Unified framework for analyzing stable learning algorithms across different dataset shifts.
Brain-computer interfaces (BCIs) have been gaining momentum in making human-computer interaction more natural, especially for people with neuro-muscular disabilities. Among the existing solutions the systems relying on electroencephalograms (EEG) occupy the most prominent place due to their non-invasiveness. However, t…
Bayesian model improves BCI performance for ALS users.
Training only BatchNorm parameters achieves surprisingly high performance in deep networks.
Paper proposes sharing models instead of data for smart health predictions.
Cost-effective models detect depression from speech.
Proposes GLWB-LTC for enhanced life care annuities with dynamic withdrawal strategies and stochastic interest rates.
Deep RNN detects FoG episodes in Parkinson's disease with high accuracy.
Neural model detects DD risk in 5-year-olds, predicting 2 years ahead.
RNNs struggle with chaotic dynamics due to exploding gradients, but we found a way to optimize training.
MKCapsnet improves schizophrenia identification using multi-kernels and dropout.
Designing of touchless user interface is gaining popularity in various contexts. Using such interfaces, users can interact with electronic devices even when the hands are dirty or non-conductive. Also, user with partial physical disability can interact with electronic devices using such systems. Research in this direct…