Camila Fernandez

false LAWRENCE, Ind. (WISH) — With freezing temperatures coming in the next couple of days, homeowners are at risk of some serious damage.

INDIANAPOLIS (WISH) — With an arctic blast heading toward Indiana, Indianapolis was preparing to have extra officers from Animal Care Services on the streets to respond to calls for pets left outside. In a few days, temperatures were expected to plummet into the single digits and below zero, which can mean life or death for […]

INDIANAPOLIS (WISH) — It goes without saying that Martin Luther King Jr. played a key role in the Civil Rights Movement, but so many more were involved.

NEW CASTLE, Ind. (WISH) — A 16-year-old is being praised by his community and firefighters for rescuing his neighbor in a house fire.

Indiana State Trooper Azariah Keith. Keith was struck and critically hurt by a vehicle on I-65 while trying to help a person change a tire. (Provided Photo/Indiana State Police)

Abortion-rights supporters say they're fighting against misinformation. They want women to know they can still choose abortion elsewhere.

The 66th Annual Grammy Awards, one of the most prestigious music awards ceremonies, will be held on February 4, 2024. One of the categories being celebrated is Best Música Mexicana Album, which includes Tejano music. Interestingly, this year’s nominations in this category are dominated by female artists, with four out of the five works being nominated belonging to them.

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Survival analysis has attracted interest from a wide range of disciplines, spanning from medicine and predictive maintenance to various industrial applications. Its growing popularity can be attributed to significant advancements in computational power and the increased availability of data. Diverse approaches have been developed to address the challenge of censored data, from classical statistical tools to contemporary machine learning techniques. However, there is still considerable room for improvement. This thesis aims to introduce innovative approaches that provide deeper insights into survival distributions and to propose new methods with theoretical guarantees that enhance prediction accuracy. Notably, we notice the lack of models able to treat sequential data, a setting that is relevant due to its ability to adapt quickly to new information and its efficiency in handling large data streams without requiring significant memory resources. The first contribution of this thesis is to propose a theoretical framework for modeling online survival data. We model the hazard function as a parametric exponential that depends on the covariates, and we use online convex optimization algorithms to minimize the negative log-likelihood of our model, an approach that is novel in this field. We propose a new adaptive second-order algorithm, SurvONS, which ensures robustness in hyperparameter selection while maintaining fast regret bounds. Additionally, we introduce a stochastic approach that enhances the convexity properties to achieve faster convergence rates. The second contribution of this thesis is to provide a detailed comparison of diverse survival models, including semi-parametric, parametric, and machine learning models. We study the dataset character- istics that influence the methods performance, and we propose an aggregation procedure that enhances prediction accuracy and robustness. Finally, we apply the different approaches discussed throughout the thesis to an industrial case study : predicting employee attrition, a fundamental issue in modern business. Additionally, we study the impact of employee characteristics on attrition predictions using permutation feature importance and Shapley values.

The Soraya (The Valley's Center for the Performing Arts)