arXiv research

Paper proposes a streamlined approach to clinical concept extraction using LSTM-CRF.

Improved named entity recognition in EHRs with transfer learning.

Personalized deep learning reduces inappropriate shocks in VA detection.

Improved financial VA intent classification accuracy.

VA-LUCB identifies best arm with variance constraint, achieving optimal sample complexity.

Objective: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can only access de-identified notes, in order to protect the confidentiality of patients. In the United States, the Health Insurance Portability a…

Spatial interpolation improves VA valuation efficiency.

Variable annuities (VA) are popular insurance products. VAs provides the insured with a guaranteed accumulation rate on their premium at maturity. In addition, the insured may receive extra benefit if returns of underlying funds are high enough. Here we consider a special case of VA with high-water mark feature and Gua…

Deep learning model extracts medical treatment-problem relationships.

New tests detect asphericity in complex pairs, simplifying previous proofs.

Study predicts lens performance using neural networks.

This paper develops a framework for predicting patient workload across multiple VA facilities.

Improves medical note processing by training model on related concepts and global context.

Study analyzes fees linked to VIX index in annuity contracts.

The paper studies Kähler groups and their virtual algebraic fibrations, finding implications for their fundamental groups.

Investigates optimal withdrawal strategies in VA contracts with tax and ratchet mechanisms.

LDP speeds up causal discovery by partitioning, improving VAS recall and runtime.

Paper develops a method for valid inference using language model predictions from verbal autopsy narratives.

Koopman models improve molecular kinetics analysis from short off-equilibrium simulations.

Managing and hedging the risks associated with Variable Annuity (VA) products require intraday valuation of key risk metrics for these products. The complex structure of VA products and computational complexity of their accurate evaluation have compelled insurance companies to adopt Monte Carlo (MC) simulations to valu…

Local discovery method uncovers direct unfairness in complex systems.

The guaranteed minimum withdrawal benefit (GMWB) rider, as an add on to a variable annuity (VA), guarantees the return of premiums in the form of peri- odic withdrawals while allowing policyholders to participate fully in any market gains. GMWB riders represent an embedded option on the account value with a fee structu…

The purpose of this article is twofold. First, we motivate the need for a new type of stand-alone retirement income insurance product that would help individuals protect against personal longevity risk and possible "retirement ruin" in an economically efficient manner. We label this product a ruin-contingent life annui…

VA-OPE improves OPE by incorporating variance information, achieving tighter error bounds.

We construct a binomial model for a guaranteed minimum withdrawal benefit (GMWB) rider to a variable annuity (VA) under optimal policyholder behaviour. The binomial model results in explicitly formulated perfect hedging strategies funded using only periodic fee income. We consider the separate perspectives of the insur…

Paper assesses GMMB in VAs using FST for accurate net liability calculations.

Paper tackles multi-task learning for emotion recognition and generation using Aff-Wild dataset.

The study examines VIX-linked fees for GMWBs using explicit solution simulation methods.

The paper uses GPR to speed up pricing of GMWB VA with stochastic vol and rate.

Deep learning model predicts human emotions in real-world settings.

This paper offers a financial economic perspective on the optimal time (and age) at which the owner of a Variable Annuity (VA) policy with a Guaranteed Living Withdrawal Benefit (GLWB) rider should initiate guaranteed lifetime income payments. We abstract from utility, bequest and consumption preference issues by treat…

Unified tensor factorization for efficient 3D convolutions in spatio-temporal emotion analysis.

In the aftermath of the 2007 global financial crisis, banks started reflecting into derivative pricing the cost of capital and collateral funding through XVA metrics. Here XVA is a catch-all acronym whereby X is replaced by a letter such as C for credit, D for debt, F for funding, K for capital and so on, and VA stands…

We prove that the homotopy class of a Morin mapping f: P^p --> Q^q with p-q odd contains a cusp mapping. This affirmatively solves a strengthened version of the Chess conjecture [DS Chess, A note on the classes [S_1^k(f)], Proc. Symp. Pure Math., 40 (1983) 221-224] and [VI Arnol'd, VA Vasil'ev, VV Goryunov, OV Lyashenk…

Study BNS invariants to prove algebraic fibrations of certain groups.

Diffusion-VAE tackles multi-step stock price prediction with stochastic noise.

We study the space of L^2 harmonic forms on complete manifolds with metrics of fibred boundary or fibred cusp type. These metrics generalize the geometric structures at infinity of several different well-known classes of metrics, including asymptotically locally Euclidean manifolds, the (known types of) gravitational i…

Neural network improves SCR calculation efficiency.

This paper analyzes a novel type of mortality contingent-claim called a ruin-contingent life annuity (RCLA). This product fuses together a path-dependent equity put option with a "personal longevity" call option. The annuitant's (i.e. long position) payoff from a generic RCLA is \$1 of income per year for life, akin to…

This work studies the class of algorithms for learning with side-information that emerge by extending generative models with embedded context-related variables. Using finite mixture models (FMM) as the prototypical Bayesian network, we show that maximum-likelihood estimation (MLE) of parameters through expectation-maxi…

Paper compares two annuity pricing models and finds insurer underestimates value.

FGTSVA improves Thompson Sampling for contextual bandits with optimal variance-aware regret.

Paper tackles BA in dual-band systems using ML.

A new Mapper algorithm optimizes data visualization through automatic parameter tuning.

The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provi…

RL faces nine challenges to apply to real-world problems.

NIST's CTS Challenge evaluates speaker recognition using telephony data.

This paper automates tagging programming challenge descriptions.