2 papers
cs.LG2023
SwiftLearn: A Data-Efficient Training Method of Deep Learning Models using Importance Sampling
Habib Hajimolahoseini, Omar Mohamed Awad, Walid Ahmed +8
In this paper, we present SwiftLearn, a data-efficient approach to accelerate training of deep learning models using a subset of data samples selected during the warm-up stages of…
cs.LG2021
Deep State Inference: Toward Behavioral Model Inference of Black-box Software Systems
Foozhan Ataiefard, Mohammad Jafar Mashhadi, Hadi Hemmati +1
Many software engineering tasks, such as testing, and anomaly detection can benefit from the ability to infer a behavioral model of the software.Most existing inference approaches…