26 citations · 87 across the 16 of their papers we have counts for
8 papers · 1 filter
Integrating Survival-Based Aging Models with Data-Driven RUL Prognostics
Abhishek Srinivasan, Juan Carlos Andresen, Sepideh Pashami +1
Predictive maintenance requires reliable remaining useful life (RUL) estimation. Existing methods mainly follow two paradigms: wear-based aging models that capture cumulative degra…
CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis
Abdallah Alabdallah, Omar Hamed, Mattias Ohlsson +2
The Cox Proportional Hazards (CPH) model has long been the preferred survival model for its explainability. However, to increase its predictive power beyond its linear log-risk, it…
Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks
Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami +2
This paper investigates how various randomization techniques impact Deep Neural Networks (DNNs). Randomization, like weight noise and dropout, aids in reducing overfitting and enha…
Forecasting Auxiliary Energy Consumption for Electric Heavy-Duty Vehicles
Yuantao Fan, Zhenkan Wang, Sepideh Pashami +2
Accurate energy consumption prediction is crucial for optimizing the operation of electric commercial heavy-duty vehicles, e.g., route planning for charging. Moreover, understandin…
Heterogeneous Federated Learning via Personalized Generative Networks
Zahra Taghiyarrenani, Abdallah Alabdallah, Slawomir Nowaczyk +1
Federated Learning (FL) allows several clients to construct a common global machine-learning model without having to share their data. FL, however, faces the challenge of statistic…
The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models
Abdallah Alabdallah, Mattias Ohlsson, Sepideh Pashami +1
The Concordance Index (C-index) is a commonly used metric in Survival Analysis for evaluating the performance of a prediction model. In this paper, we propose a decomposition of th…
Surrogate-Assisted Genetic Algorithm for Wrapper Feature Selection
Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami +1
Feature selection is an intractable problem, therefore practical algorithms often trade off the solution accuracy against the computation time. In this paper, we propose a novel mu…
Pitfalls of Assessing Extracted Hierarchies for Multi-Class Classification
Pablo del Moral, Slawomir Nowaczyk, Anita Sant'Anna +1
Using hierarchies of classes is one of the standard methods to solve multi-class classification problems. In the literature, selecting the right hierarchy is considered to play a k…