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
Enhancing Malware Detection by Integrating Machine Learning with Cuckoo Sandbox
Amaal F. Alshmarni, Mohammed A. Alliheedi
Extending Machine Learning-Based Early Sepsis Detection to Different Demographics
Surajsinh Parmar, Tao Shan, San Lee, Yonghwan Kim, Jang Yong Kim
On Leakage in Machine Learning Pipelines
Leonard Sasse, Eliana Nicolaisen-Sobesky, Juergen Dukart, Simon B. Eickhoff, Michael Götz, Sami Hamdan, Vera Komeyer, Abhijit Kulkarni, Juha Lahnakoski, Bradley C. Love, Federico Raimondo, Kaustubh R. Patil
Personality Style Recognition via Machine Learning: Identifying Anaclitic and Introjective Personality Styles from Patients' Speech
Semere Kiros Bitew, Vincent Schelstraete, Klim Zaporojets, Kimberly Van Nieuwenhove, Reitske Meganck, Chris Develder
MatNexus: A Comprehensive Text Mining and Analysis Suite for Materials Discover
Lei Zhang, Markus Stricker
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
Machine Learning Parameterization of the Multi-scale Kain-Fritsch (MSKF) Convection Scheme
Xiaohui Zhong, Xing Yu, Hao Li
Innovation and Word Usage Patterns in Machine Learning
Vítor Bandeira Borges, Daniel Oliveira Cajueiro
Discretizing Numerical Attributes: An Analysis of Human Perceptions
Minakshi Kaushik, Rahul Sharma, Dirk Draheim
End-to-end Material Thermal Conductivity Prediction through Machine Learning
Yagyank Srivastava, Ankit Jain
Algebraic Dynamical Systems in Machine Learning
Iolo Jones, Jerry Swan, Jeffrey Giansiracusa
SoK: Memorisation in machine learning
Dmitrii Usynin, Moritz Knolle, Georgios Kaissis
Exploring Best Practices for ECG Signal Processing in Machine Learning
Amir Salimi, Sunil Vasu Kalmady, Abram Hindle, Osmar Zaiane, Padma Kaul
An Efficient Detection and Control System for Underwater Docking using Machine Learning and Realistic Simulation: A Comprehensive Approach
Jalil Chavez-Galaviz, Jianwen Li, Matthew Bergman, Miras Mengdibayev, Nina Mahmoudian