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

December 3, 2024

Optimized IoT Intrusion Detection using Machine Learning Technique
Muhammad Zawad Mahmud, Samiha Islam, Shahran Rahman Alve, Al Jubayer Pial
Machine Learning Random Forest Intrusion Detection System IoT Intrusion Detection
WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks
Rajat Shinde, Christopher E. Phillips, Kumar Ankur, Aman Gupta, Simon Pfreundschuh, Sujit Roy, Sheyenne Kirkland, Vishal Gaur, Amy Lin, Aditi Sheshadri, Udaysankar Nair, Manil Maskey, Rahul Ramachandran
Machine Learning High Quality Downstream Task Novel Dataset Virtual Analog
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management
Weiche Hsieh, Ziqian Bi, Keyu Chen, Benji Peng, Sen Zhang, Jiawei Xu, Jinlang Wang, Caitlyn Heqi Yin, Yichao Zhang, Pohsun Feng, Yizhu Wen, Tianyang Wang, Ming Li, Chia Xin Liang, Jintao Ren, Qian Niu, Silin Chen, Lawrence K.Q. Yan, Han Xu, Hong-Ming Tseng, Xinyuan Song, Bowen Jing, Junjie Yang, Junhao Song, Junyu Liu, Ming Liu
Deep Learning Machine Learning Big Data
Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach
Tony T. Wang, John Hughes, Henry Sleight, Rylan Schaeffer, Rajashree Agrawal, Fazl Barez, Mrinank Sharma, Jesse Mu, Nir Shavit, Ethan Perez
Machine Learning Adversarial Training NCD Method Domain Specific Jailbreak Attack Fundamental Limitation Stochastic Defense
Machine Learning Methods for Automated Interstellar Object Classification with LSST
Richard Cloete, Peter Vereš, Abraham Loeb
Machine Learning Classification Code Scientific Discovery Simulated Data Data Analysis Pipeline State of the Art Tracklets
Evaluating the Impact of Data Augmentation on Predictive Model Performance
Valdemar Švábenský, Conrad Borchers, Elizabeth B. Cloude, Atsushi Shimada
Machine Learning Data Augmentation Global Impact System Performance Predictive Model Data Augmentation Technique Augmentation Technique
BN-AuthProf: Benchmarking Machine Learning for Bangla Author Profiling on Social Media Texts
Raisa Tasnim, Mehanaz Chowdhury, Md Ataur Rahman
Machine Learning Social Medium Authorship Analysis Co Writing

December 2, 2024

Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques
Soheila Sadeghi
Machine Learning Global Impact Task Scheduling Hidden CoST Scope Sensitive Computer Assisted Project
Identifying Key Nodes for the Influence Spread using a Machine Learning Approach
Mateusz Stolarski, Adam Piróg, Piotr Bródka
Machine Learning Constructive Approach Complex Network Cascade Model Centrality Measure Influential Node
Kernel-Free Universum Quadratic Surface Twin Support Vector Machines for Imbalanced Data
Hossein Moosaei, Milan Hladík, Ahmad Mousavi, Zheming Gao, Haojie Fu
Machine Learning Supervised Learning Support Vector Machine Binary Classification Imbalanced Data Imbalanced Classification
Characterizing Jupiter's interior using machine learning reveals four key structures
Maayan Ziv, Eli Galanti, Saburo Howard, Tristan Guillot, Yohai Kaspi
Machine Learning Inner Structure Indoor Environment Parameter Distribution Gravity Model
Harnessing Preference Optimisation in Protein LMs for Hit Maturation in Cell Therapy
Katarzyna Janocha, Annabel Ling, Alice Godson, Yulia Lampi, Simon Bornschein, Nils Y. Hammerla
Machine Learning Accurate Treatment Protein Engineering Cell Center Hitting Time Subcutaneous Immunotherapy
Research on Optimizing Real-Time Data Processing in High-Frequency Trading Algorithms using Machine Learning
Yuxin Fan, Zhuohuan Hu, Lei Fu, Yu Cheng, Liyang Wang, Yuxiang Wang
Machine Learning Feature Selection DH Research High Frequency Financial Market Algorithmic Trading Real Time Processing
Embedded Machine Learning for Solar PV Power Regulation in a Remote Microgrid
Yongli Zhu, Linna Xu, Jian Huang
Machine Learning Machine Learning Model DC Microgrid Application Remote Human Operator Embedded Neural Network Based Volt Var Control

November 30, 2024

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning
Andrew Root, Liam Jakubowski, Mounika Vanamala
Machine Learning Machine Learning Model Global Evaluation Absolute Stance Bias Environment Exploration Unseen Data Cross Dataset Data Curation Cyberbullying Detection
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina J. Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Stuart B. Dalziel, Drummond B. Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich R. Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, François Rozet, Liam H. Parker, Miles Cranmer, Shirley Ho
Machine Learning Surrogate Model Fluid Dynamic Numerical Simulation Spatiotemporal Dynamical System Large Collection Physic Simulation MagnetoHydroDynamics Simulation
On the Conditions for Domain Stability for Machine Learning: a Mathematical Approach
Gabriel Pedroza
Machine Learning Machine Learning Model Adverse Condition Metric Space Classification Datasets

Machine Learning

Papers

Beyond algorithm hyperparameters: on preprocessing hyperparameters and associated pitfalls in machine learning applications

Unified Inductive Logic: From Formal Learning to Statistical Inference to Supervised Learning

How Many Ratings per Item are Necessary for Reliable Significance Testing?

Optimized IoT Intrusion Detection using Machine Learning Technique

WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks

Deep Learning, Machine Learning, Advancing Big Data Analytics and Management

Jailbreak Defense in a Narrow Domain: Limitations of Existing Methods and a New Transcript-Classifier Approach

Machine Learning Methods for Automated Interstellar Object Classification with LSST

Evaluating the Impact of Data Augmentation on Predictive Model Performance

BN-AuthProf: Benchmarking Machine Learning for Bangla Author Profiling on Social Media Texts

Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques

Identifying Key Nodes for the Influence Spread using a Machine Learning Approach

Kernel-Free Universum Quadratic Surface Twin Support Vector Machines for Imbalanced Data

Characterizing Jupiter's interior using machine learning reveals four key structures

Harnessing Preference Optimisation in Protein LMs for Hit Maturation in Cell Therapy

Research on Optimizing Real-Time Data Processing in High-Frequency Trading Algorithms using Machine Learning

Embedded Machine Learning for Solar PV Power Regulation in a Remote Microgrid

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning

On the Conditions for Domain Stability for Machine Learning: a Mathematical Approach