Machine Learning
Machine learning (ML) focuses on developing algorithms that allow computers to learn from data without explicit programming, aiming to improve prediction accuracy, automate tasks, and extract insights. Current research emphasizes areas like fairness in federated learning, efficient model training and deployment (including techniques to reduce communication overhead), and enhancing model interpretability and robustness against adversarial attacks. ML's impact spans diverse fields, from healthcare (e.g., disease prediction) and industrial quality control to astrophysics (e.g., galaxy classification) and cybersecurity, demonstrating its broad applicability and significant potential for scientific advancement and practical problem-solving.
Papers
An AI-Driven Data Mesh Architecture Enhancing Decision-Making in Infrastructure Construction and Public Procurement
Saurabh Mishra, Mahendra Shinde, Aniket Yadav, Bilal Ayyub, Anand Rao
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations
Attila Cangi, Lenz Fiedler, Bartosz Brzoza, Karan Shah, Timothy J. Callow, Daniel Kotik, Steve Schmerler, Matthew C. Barry, James M. Goff, Andrew Rohskopf, Dayton J. Vogel, Normand Modine, Aidan P. Thompson, Sivasankaran Rajamanickam
Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education
Anamaria Mojica-Hanke, David Nader Palacio, Denys Poshyvanyk, Mario Linares-Vásquez, Steffen Herbold
Deep Neural Network-Based Prediction of B-Cell Epitopes for SARS-CoV and SARS-CoV-2: Enhancing Vaccine Design through Machine Learning
Xinyu Shi, Yixin Tao, Shih-Chi Lin
Learning optimal objective values for MILP
Lara Scavuzzo, Karen Aardal, Neil Yorke-Smith
Randomized-Grid Search for Hyperparameter Tuning in Decision Tree Model to Improve Performance of Cardiovascular Disease Classification
Abhay Kumar Pathak, Mrityunjay Chaubey, Manjari Gupta
The Return of Pseudosciences in Artificial Intelligence: Have Machine Learning and Deep Learning Forgotten Lessons from Statistics and History?
Jérémie Sublime
Enhancing Project Performance Forecasting using Machine Learning Techniques
Soheila Sadeghi
Automating grapevine LAI features estimation with UAV imagery and machine learning
Muhammad Waseem Akram, Marco Vannucci, Giorgio Buttazzo, Valentina Colla, Stefano Roccella, Andrea Vannini, Giovanni Caruso, Simone Nesi, Alessandra Francini, Luca Sebastiani
Machine Learning and Multi-source Remote Sensing in Forest Carbon Stock Estimation: A Review
Autumn Nguyen, Sulagna Saha
From Machine Learning to Machine Unlearning: Complying with GDPR's Right to be Forgotten while Maintaining Business Value of Predictive Models
Yuncong Yang, Xiao Han, Yidong Chai, Reza Ebrahimi, Rouzbeh Behnia, Balaji Padmanabhan
Deciphering Acoustic Emission with Machine Learning
Dénes Berta, Balduin Katzer, Katrin Schulz, Péter Dusán Ispánovity
Machine Learning for the Digital Typhoon Dataset: Extensions to Multiple Basins and New Developments in Representations and Tasks
Asanobu Kitamoto, Erwan Dzik, Gaspar Faure
Machine learning for cerebral blood vessels' malformations
Irem Topal, Alexander Cherevko, Yuri Bugay, Maxim Shishlenin, Jean Barbier, Deniz Eroglu, Édgar Roldán, Roman Belousov
Cluster-based human-in-the-loop strategy for improving machine learning-based circulating tumor cell detection in liquid biopsy
Hümeyra Husseini-Wüsthoff, Sabine Riethdorf, Andreas Schneeweiss, Andreas Trumpp, Klaus Pantel, Harriet Wikman, Maximilian Nielsen, René Werner
Diagnosis of diabetic retinopathy using machine learning & deep learning technique
Eric Shah, Jay Patel, Mr.Vishal Katheriya, Parth Pataliya
Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning
Rajib Rana, Niall Higgins, Kazi Nazmul Haque, John Reilly, Kylie Burke, Kathryn Turner, Terry Stedman
Understanding Machine Learning Paradigms through the Lens of Statistical Thermodynamics: A tutorial
Star (Xinxin)Liu
An AutoML-based approach for Network Intrusion Detection
Nana Kankam Gyimah, Judith Mwakalonge, Gurcan Comert, Saidi Siuhi, Robert Akinie, Methusela Sulle, Denis Ruganuza, Benibo Izison, Arthur Mukwaya
A review on Machine Learning based User-Centric Multimedia Streaming Techniques
Monalisa Ghosh, Chetna Singhal