Md. Fahim

Work place: Department of Computer Science and Engineering, University of Dhaka, Dhaka-1000, Bangladesh

E-mail: fahimcse381@gmail.com

Website:

Research Interests:

Biography

Md Fahim received his B.Sc Degree in Computer Science from the University of Dhaka. He is currently serving as a Research Assistant at the Center for Computation and Data Sciences (CCDS Lab) at Independent University, Bangladesh. His research interests primarily lie in the fields of NLP, explainability, and low resource languages along with learning-to-rank domain. With a focus on advancing these areas, he has contributed significantly to the field, having authored five first-author conference publications.

Author Articles
An Exploratory Study on Simulated Annealing for Feature Selection in Learning-to-rank

By Mohd. Sayemul Haque Md. Fahim Muhammad Ibrahim

DOI: https://doi.org/10.5815/ijisa.2024.04.06, Pub. Date: 8 Aug. 2024

Learning-to-rank is an applied domain of supervised machine learning. As feature selection has been found to be effective for improving the accuracy of learning models in general, it is intriguing to investigate this process for learning-to-rank domain. In this study, we investigate the use of a popular meta-heuristic approach called simulated annealing for this task. Under the general framework of simulated annealing, we explore various neighborhood selection strategies and temperature cooling schemes. We further introduce a new hyper-parameter called the progress parameter that can effectively be used to traverse the search space. Our algorithms are evaluated on five publicly benchmark datasets of learning-to-rank. For a better validation, we also compare the simulated annealing-based feature selection algorithm with another effective meta-heuristic algorithm, namely local beam search. Extensive experimental results show the efficacy of our proposed models.

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