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 Efficient Contrastive Unimodal Pretraining Method for EHR Time Series Data
Ryan King, Shivesh Kodali, Conrad Krueger, Tianbao Yang, Bobak J. Mortazavi
Time to Retrain? Detecting Concept Drifts in Machine Learning Systems
Tri Minh Triet Pham, Karthikeyan Premkumar, Mohamed Naili, Jinqiu Yang
Learning Algorithms Made Simple
Noorbakhsh Amiri Golilarz, Elias Hossain, Abdoljalil Addeh, Keyan Alexander Rahimi
Bank Loan Prediction Using Machine Learning Techniques
F M Ahosanul Haque, Md. Mahedi Hassan
A Systematic Survey on Large Language Models for Algorithm Design
Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang
SOAK: Same/Other/All K-fold cross-validation for estimating similarity of patterns in data subsets
Toby Dylan Hocking, Gabrielle Thibault, Cameron Scott Bodine, Paul Nelson Arellano, Alexander F Shenkin, Olivia Jasmine Lindly
MYCROFT: Towards Effective and Efficient External Data Augmentation
Zain Sarwar, Van Tran, Arjun Nitin Bhagoji, Nick Feamster, Ben Y. Zhao, Supriyo Chakraborty
Machine Learning for Missing Value Imputation
Abu Fuad Ahmad, Khaznah Alshammari, Istiaque Ahmed, MD Shohel Sayed
Impact of Missing Values in Machine Learning: A Comprehensive Analysis
Abu Fuad Ahmad, Md Shohel Sayeed, Khaznah Alshammari, Istiaque Ahmed
Active Fourier Auditor for Estimating Distributional Properties of ML Models
Ayoub Ajarra, Bishwamittra Ghosh, Debabrota Basu
Machine Learning-based feasibility estimation of digital blocks in BCD technology
Gabriele Faraone, Francesco Daghero, Eugenio Serianni, Dario Licastro, Nicola Di Carolo, Michelangelo Grosso, Giovanna Antonella Franchino, Daniele Jahier Pagliari
MEMS Gyroscope Multi-Feature Calibration Using Machine Learning Technique
Yaoyao Long, Zhenming Liu, Cong Hao, Farrokh Ayazi
Stress Detection on Code-Mixed Texts in Dravidian Languages using Machine Learning
L. Ramos, M. Shahiki-Tash, Z. Ahani, A. Eponon, O. Kolesnikova, H. Calvo
FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications
Nga Pham, Minh Kha Do, Tran Vu Dai, Pham Ngoc Hung, Anh Nguyen-Duc
CAP: Detecting Unauthorized Data Usage in Generative Models via Prompt Generation
Daniela Gallo, Angelica Liguori, Ettore Ritacco, Luca Caviglione, Fabrizio Durante, Giuseppe Manco
Predicting Fine-grained Behavioral and Psychological Symptoms of Dementia Based on Machine Learning and Smart Wearable Devices
Benny Wei-Yun Hsu, Yu-Ming Chen, Yuan-Han Yang, Vincent S. Tseng
Understanding with toy surrogate models in machine learning
Andrés Páez