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• Control Theories for Machine Learning Algorithms Analysis and Design (CT4ML): An Overview of A Short Course
  crossref Yangquan Chen 2026-06-12T14:50:39Z 置信度 0.70
• Data-driven optimization: efficient adaptive learning for self-driving laboratories
  Self-driving laboratories promise to compress materials-discovery timelines from years to weeks by replacing trial-and-error experimentation with closed-loop, algorithm-guided campaigns. Yet, despite the rapid proliferation of robotic and automation hardware, …
  crossref Nick Sahinidis 2026-07-13T13:28:36Z 置信度 0.70
• Research on Automatic Financial Statement Audit Algorithm Integrating Deep Learning and Machine Learning
  crossref Shuyao Ren 2026-03-27T19:48:32Z 置信度 0.70
• Overview of Machine Learning and Deep Learning Algorithms
  crossref Ramkumar Rajabathar Babu Jai Shanker, Daniel Thomas Ginat 2026-08-11T22:19:53Z 置信度 0.70
• Introduction of Machine Learning
  crossref Jingli Ren, Yiwen Tao 2026-02-11T16:33:50Z 置信度 0.70
• Revolutionizing Project Delivery and Success Rates through AI and Machine Learning
  crossref RaviKumar Bhuvanagiri 2026-01-30T15:37:18Z 置信度 0.70
• Reinforcement learning in process design
  crossref Uzma Hira, Umm-e-Farwa Mazhar, Isra Tasawar, Nimra Maqsood 等 2026-06-26T13:32:30Z 置信度 0.70
• Anticipating Tipping with Adaptable Reservoir Computing
  crossref 2026-06-17T03:29:03Z 置信度 0.70
• Support vector machine, an important supervised learning category
  crossref Prateek Mathur 2026-02-06T09:32:45Z 置信度 0.70
• A Machine Learning-Based Tropical Cyclone Precipitation Simulation in China
  Heavy precipitation is a major hazard associated with tropical cyclones, often causing substantial economic losses and casualties through secondary disasters such as floods, landslides, and debris flows. The southeastern coast of China is one of the region mos…
  crossref Kai Tao, Wei Xu 2026-03-13T23:03:52Z 置信度 0.70
• Bibliography
  crossref 2026-07-26T00:05:30Z 置信度 0.70
• Decision letter for "A Machine Learning-Based Workflow for Transaminase Selection"
  crossref 2026-05-20T21:01:28Z 置信度 0.70
• Review for "Bridging Structure and Activity in Nanocatalysts via Machine Learning and Global Structure Representations"
  crossref 2026-07-16T21:10:25Z 置信度 0.70
• AI Benefits and Machine Learning Errors - Neurology, Psychiatry and Neurosurgery
  Abstract Background AI is used in analysis, treatment planning, surgical and surgical neuroscience, psychiatry, and neurosurgery. However, the system may cause misdiagnosis or damage to gain knowledge of faults. Methods We systematically searched PubMed, Scopu…
  crossref Saif M. Hassan 2026-06-26T07:00:11Z 置信度 0.70
• Predictive Analytics for Compliance Optimization: Machine Learning Applications in Digital Platform Operations
  This paper examines the application of machine learning techniques to improve operational efficiency in large-scale digital platform environments. It develops a predictive analytics framework to estimate enforcement likelihood within platform compliance workfl…
  crossref Samvit Yadav 2026-07-29T13:27:33Z 置信度 0.70
• Decision letter for "Robust Machine Learning Prediction of Surface Roughness in SKD61 Turning"
  crossref 2026-08-11T21:05:08Z 置信度 0.70
• Deep learning prediction of EHL friction using full surface roughness profiles: An LSTM-MLP approach
  crossref Sheng Li 2026-03-04T19:56:22Z 置信度 0.70
• Small-data machine learning for resolving degradation challenges in energy devices
  Degradation is a central bottleneck for deploying next-generation energy devices, yet generating large, long-duration aging datasets is costly and slow. This Perspective surveys small-data machine learning (ML) techniques that extract maximal information from …
  crossref Shuan Cheng, Xiao Cui, Hemanth Neelgund Ramesh, William C. Chueh 等 2026-05-05T13:42:12Z 置信度 0.70
• Optimizing Fraud Detection Systems in Credit Card Transactions Using Machine Learning Techniques
  crossref Veerendra Reddy, T. Rathidevi, Boppuru Rudra Prathap 2026-01-05T10:21:52Z 置信度 0.70
• Evaluating Machine Learning Algorithms for Automated Personality Judgment
  crossref Rajiv Kumar 2026-02-02T16:25:02Z 置信度 0.70
• Logistic Regression: From Sigmoid Curves to Classification Boundaries
  crossref Weisheng Jiang 2026-07-31T10:55:03Z 置信度 0.70
• Explainability and Interpretability in Machine Learning and Artificial Intelligence
  Summary For over a century, linear regression served as the primary tool for data analysis. Because partial differentiation with respect to explanatory variables yielded their coefficients as partial effects, regression was inherently interpretable, directly d…
  crossref Colin Rowat 2026-06-18T18:14:36Z 置信度 0.70
• Review for "Machine Learning-Enhanced Identification of Fluorophilic Interactions for Improved SERS Detection of PFOA"
  crossref 2026-02-20T21:04:29Z 置信度 0.70
• Transforming Disease Diagnosis: A Comparison of Traditional and Machine Learning-Based Methods
  This paper presents a comparative analysis of traditional diagnostic methods and machine learning approaches across six prevalent chronic diseases: Cancer, Obesity, Diabetes, Arthritis, Asthma, and Hypertension. Using a dataset of 55,000+ patient records compr…
  crossref Pramathesh Shukla 2026-06-04T14:04:31Z 置信度 0.70
• A machine learning approach for detecting biofouling in oceanographic data
  Abstract. Autonomous ocean observing platforms collect long-term biogeochemical time series, but sensor degradation from biofouling introduces progressive biases that contaminate the climate record. This work focuses on the BGC-Argo fleet of profiling floats, …
  crossref Ourania Giannopoulou 2026-07-31T12:32:03Z 置信度 0.70
• Review for "Achieving a Scalable Machine Learning Workflow for Crystal Structure Discovery with Experimental Validations"
  crossref 2026-05-26T07:48:36Z 置信度 0.70
• Machine Learning for Sustainable Energy Solutions
  crossref 2025-12-19T21:25:58Z 置信度 0.70
• Resolution Matters More Than Attention: Super-Resolution Preprocessing for Accurate Infrared Tiny Target Detection Using YOLOv8s
  crossref Krunal Dhanraj Randive, J. Satya Sai Kumar 2026-06-22T20:05:15Z 置信度 0.70
• Neuromorphic technologies for novel hardware AI
  crossref Gianluca Milano, Giacomo Pedretti, Nagarajan Raghavan 2026-07-08T19:29:48Z 置信度 0.70
• Artificial Intelligence and Machine Learning in Cyber Defence
  crossref S.R. Purkar 2026-02-26T07:06:55Z 置信度 0.70
• Machine Learning: concepts and foundations
  crossref 2026-08-13T11:26:20Z 置信度 0.70
• Distance Measures in Data – Understanding Similarity and Difference
  crossref Weisheng Jiang 2026-07-31T10:55:03Z 置信度 0.70
• Building AI Systems with Python
  crossref Martin Hander 2026-07-30T12:44:40Z 置信度 0.70
• Index
  crossref 2026-05-18T14:39:18Z 置信度 0.70
• Machine Learning Algorithms
  crossref Ajit Pandey, Pramod Gupta, Naresh Kumar Sehgal 2026-04-30T22:23:02Z 置信度 0.70
• Background: Machine Learning and Energy
  crossref 2026-03-11T03:54:33Z 置信度 0.70
• Machine learning-driven approach to understanding punching shear design in steel fibre-reinforced slabs
  Predicting the punching shear strength of steel fibre-reinforced concrete (SFRC) slabs is crucial to the design process and structural safety. Traditional design codes, such as ACI 318-19 (ACI, 2019), Canadian Standards Association (CSA) and Eurocode 2 (BSI, 2…
  crossref Asad S Albostami, Rwayda Kh S Al-Hamd 2026-05-18T14:39:18Z 置信度 0.70
• Early Stage Mental Health Screening for Students using Machine Learning Techniques
  crossref Priyanki Dutta, Sahil Dudhoria, Tridib Paul, Anal Acharya 等 2026-04-13T07:45:45Z 置信度 0.70
• Explainable Multimodal Quantum Learning Based Model for Autism Spectrum Disorder Classification
  crossref Jagadesh Balasubramani, Surendran R 2026-05-01T19:51:20Z 置信度 0.70
• Review for "Higher-order phonon scattering and lattice thermal conductivity prediction via machine learning"
  crossref 2026-05-26T07:12:33Z 置信度 0.70
• Poster: Machine learning applications for drug discover
  To aid drug discovery in neurodegeneration, we created four unique computational methodologies, leveraging the capabilities of scikit-learn and PyTorch. Despite being developed for neurodegeneration, these methodologies hold potential for application in other …
  crossref Mariya Ivanova 2026-05-21T14:15:55Z 置信度 0.70
• Review for "Machine Learning Aided Design of Reversible MXene Electrocatalysts for Li-Air Batteries"
  crossref 2026-03-24T21:14:44Z 置信度 0.70
• Intelligent CI/CD Pipeline Optimization Using Machine Learning-Based DevOps Automation
  The rapid evolution of software development practices necessitates sophisticated approaches to Continuous Integration and Continuous Deployment (CI/CD) pipeline optimization. This research article presents a comprehensive framework for intelligent CI/CD pipeli…
  crossref Aishat Gbemi 2026-03-10T10:00:35Z 置信度 0.70
• Predicting the Green Purchase Intention of Generation Z Café Consumers in Manila Using Machine Learning Techniques
  crossref Chelsee Bustos, Kirk Nathaniel Gamorot, Cassey Panganiban, Alexander Hernandez 等 2026-08-10T19:09:21Z 置信度 0.70
• Lifestyle and Symptom-Based Early Detection of Polycystic Ovary Syndrome Using Machine Learning
  crossref Kavipriyanga S U, Aishwarya S S, V. R. Sadasivam 2026-05-22T19:33:52Z 置信度 0.70
• Machine Learning Approaches for Predicting Stribeck Curves in Lubricated Contacts
  Abstract Machine elements frequently operate under variable conditions, resulting in significant variations in interfacial friction across different lubrication regimes. The Stribeck curve is a well-established tool for visualizing frictional behavior under bo…
  crossref Pedro Romio 2026-04-22T08:45:28Z 置信度 0.70
• Integrating AI and Machine Learning (ML) with the Internet of Things (IoT)
  crossref T. A. Swetha Margaret, D. Renuka Devi, I. Diana Judith 2026-05-22T21:19:27Z 置信度 0.70
• Machine learning-guided mechanical characterisation of 3D-printed plastic materials towards future optimisation of additive manufactured infrastructure components
  Machine learning (ML)-guided materials design is a powerful tool in advancing additive manufacturing (AM) processes. ML-guided materials design involves using ML methods to analyse/model the relationships between the composition, structure and properties of ma…
  crossref Rashmi Bhaila, Hadi Salehi 2026-05-18T14:39:18Z 置信度 0.70
• Data curation strategies for geospatial machine learning: a case study in peatland classification
  crossref Louis Saumier, Joe R Melton, Scott Winton 2026-06-26T22:47:54Z 置信度 0.70
• Adaptive Machine Learning Protocol for DDoS Attack Detection in Cloud Computing
  crossref Kedar Nath Singh, Kuldeep Kumar Kushwaha, Balwant Singh Raghuwanshi, Ashok Kumar Mishra 等 2026-06-08T19:49:34Z 置信度 0.70
• Challenges and Limitations of Machine Learning Models in Financial Volatility Prediction
  Over the years, machine learning has been increasingly positioned as a way to make sense of this uncertainty. Flexible models, large datasets, and improved computation have created the impression that volatility can now be forecast with reasonable confidence. …
  crossref Abdullah Attarwala 2026-03-10T10:11:19Z 置信度 0.70
• Responsible Machine Learning Operations: Closing The Gap Between Speed And Oversight
  crossref Andrew Beckstrand 2026-01-26T16:19:34Z 置信度 0.70
• Intelligent Prediction of EFL Student Performance in Higher Education Using Ensemble Machine Learning Techniques
  crossref 2026-07-31T11:56:24Z 置信度 0.70
• Integrating Machine Learning and Remote Sensing for Accurate Hail Damage Forecasting
  crossref Tiffany Caleb 2026-01-26T12:30:51Z 置信度 0.70
• KernelAegis: Predictive Anomaly Detection for Linux Kernel Behavior Using Machine Learning
  crossref Aditya Singh 2026-01-21T14:10:27Z 置信度 0.70
• Comparing Machine Learning Models of Raindrop Formation
  The simplest model, based on polynomials, yields the best performance.
  crossref Nathaniel Scharping 2026-07-09T07:00:18Z 置信度 0.70
• Developing a modern Fortran statistics and machine learning library (FSML) 
  Advances in computing, statistics, and machine learning (ML) techniques have significantly changed research practices across disciplines. Despite Fortran’s continued importance in scientific computing and long history in data-driven prediction, its statistics …
  crossref Sebastian G. Mutz 2026-03-13T21:26:36Z 置信度 0.70
• Review for "Machine learning to predict plasma-based CO2 conversion in dielectric barrier discharges"
  crossref 2026-05-14T21:11:23Z 置信度 0.70
• Review for "Machine learning to predict plasma-based CO2 conversion in dielectric barrier discharges"
  crossref 2026-05-14T21:11:23Z 置信度 0.70
• Generalized Multivariate Gaussian Distribution in Machine Learning for Industrial Anomaly Detection
  In the field of Machine Learning (ML), transitioning from univariate monitoring to a multivariate framework allows for a sophisticated analysis of complex industrial systems. While bivariate models evaluate two related sensors, the generalized multivariate Gau…
  crossref Chinnaraji Annamalai 2026-05-23T12:44:37Z 置信度 0.70
• Optimisation of Production Planning Through Machine Learning Techniques
  In the fast-paced manufacturing environment of today, working out the right way to plan production has become one of the toughest puzzles faced by industrial systems. Demand keeps shifting, available resources are tight, and there is constant pressure to run o…
  crossref Mauli Karande Prakash, RameshD Jadhav 2026-05-28T08:03:43Z 置信度 0.70
• The Tweed Mapping Project: machine learning methods for rapid Quaternary mapping
  When large areas of the UK were mapped over 100 years ago priority was given to identification of mineral resources. Many such ‘drift’ maps therefore are not consistent with modern scientific understanding, nor do they reflect current stakeholder interests. Su…
  crossref Sam Roberson 2026-03-14T02:15:54Z 置信度 0.70
• Introduction
  crossref Dennis Tay 2026-08-17T10:45:31Z 置信度 0.70
• Machine Learning, Real-time Macroeconomic Risk, and Asset Pricing
  This paper develops a state-dependent asset pricing framework that measures and prices macroeconomic risk in real time by integrating a structural long-run risk model with high-frequency textual information. Our primary methodological contribution is to recove…
  crossref Adelphe Ekponon, Aaron Tormeti 2026-07-29T13:47:31Z 置信度 0.70
• Machine Learning Meets Markowitz
  crossref Yijie Wang, Hao Gao, Campbell Harvey, Yan Liu 等 2026-02-24T00:32:11Z 置信度 0.70
• Review for "Developing a Machine-Learning Interatomic Potential for Non-Covalent Interactions in Proteins"
  crossref 2026-06-08T15:13:01Z 置信度 0.70
• Real Alteryx-Machine-Learning-Fundamentals Exam Questions – Smart Way to Pass Certification
  crossref Max Markey 2026-02-21T10:30:26Z 置信度 0.70
• Optimising thermal pressing of airlaids with machine learning
  Airlaying is a promising alternative to conventional papermaking that does not require extensive drying. The key limitation of airlaids is weak fiber bonding, which results in low strength. Strength can be improved with thermal pressing, which however involves…
  crossref Hannu Rummukainen, Tuomo Hjelt, Mikko Mäkelä 2026-02-17T09:31:08Z 置信度 0.70
• Design of 2D material integrated optical polarizers using machine learning
  Abstract On-chip integration of highly anisotropic two-dimensional (2D) materials offers new opportunities for realizing high-performance polarization-selective devices. Obtaining optimized designs for such devices requires extensively sweeping large parameter…
  crossref dave moss 2026-02-19T11:27:01Z 置信度 0.70
• Review for "Supply Chain Optimisation Using Physics-Informed Machine Learning for Digital Product Passport"
  crossref 2026-07-10T21:09:02Z 置信度 0.70
• Machine Learning Rediscovers Equations Governing Ocean Biogeochemistry
  Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.
  crossref Nathaniel Scharping 2026-06-25T07:00:17Z 置信度 0.70
• Advances and Applications of Machine Learning in Fluid Flow Problems
  crossref Mohamed El-Amin 2026-03-06T14:09:53Z 置信度 0.70
• Double debiased machine learning nonparametric inference with continuous treatments
  crossref Kyle Colangelo, Ying-Ying Lee 2019-10-21T05:12:35Z 置信度 0.70
• Artificial Intelligence and Machine Learning for Personalized Nutrition and Health Management
  The increasing global burden of diet-related chronic diseases and the limitations of conventional "one-size-fitsall" dietary guidelines highlight the urgent need for data-driven approaches to personalized nutrition and health management. Artificial intelligenc…
  crossref Harshita Gupta 2026-03-16T14:20:15Z 置信度 0.70
• Designing Machine Learning Error-Mitigation Protocols for High-Fidelity Digital Quantum Simulation
  The pursuit of high-fidelity digital quantum simulation is fundamentally constrained by the inevitable presence of noise in current and near-term quantum processors. While quantum error correction ultimately promises fault-tolerance, its substantial qubit over…
  crossref Albert Schmidt 2026-07-17T09:05:13Z 置信度 0.70
• Machine Learning and Blockchain – Challenges, Future Trends and Sustainable Technologies
  With contributions from leading researchers and industry experts, this book examines cutting-edge applications, integration models, and sustainable solutions across sectors including finance, agriculture, healthcare, IoT, and smart cities. Chapters cover block…
  crossref 2026-01-15T11:48:36Z 置信度 0.70
• About the Editors
  crossref 2026-03-08T14:57:25Z 置信度 0.70
• Customer Churn Prediction Using Machine Learning
  Customer churn is a common problem for businesses that depend on keeping customers for a long period of time. This includes industries such as telecommunications, banking, insurance, subscription services, and online platforms. Customer churn happens when an e…
  crossref Kim Min Joon, Fatima Al Mansoori 2026-08-26T14:04:45Z 置信度 0.70
• Machine Learning in Drug-induced Adverse Reaction Modeling: Case Studies of Drug-induced Cardiotoxicity Modeling
  Drug-induced cardiotoxicity is a major safety concern across all stages of drug discovery and development. Experimental methods, including in vitro assays and animal testing, are time-consuming, expensive, and may not fully predict cardiotoxicity in humans. Ma…
  crossref Jie Liu, Wenjing Guo, Tucker A. Patterson, Huixiao Hong 2026-07-22T08:41:26Z 置信度 0.70
• Index
  crossref 2025-12-22T14:47:04Z 置信度 0.70
• Review for "Developing a Machine-Learning Interatomic Potential for Non-Covalent Interactions in Proteins"
  crossref 2026-06-08T15:13:01Z 置信度 0.70
• Classification Trees
  crossref Yinglin Xia, Jun Sun 2026-01-17T03:25:26Z 置信度 0.70
• Sustainable Applications for Machine Learning
  crossref 2026-04-13T05:36:04Z 置信度 0.70
• Review for "Higher-order phonon scattering and lattice thermal conductivity prediction via machine learning"
  crossref 2026-05-26T07:12:33Z 置信度 0.70
• Morphology-Correlated Machine Learning for Quantitative SERS Detection
  We demonstrated that morphology-correlated SERS integrated with support vector regression on a biological photonic crystal slab enables robust quantification of trace fentanyl, achieving high accuracy with a wide dynamic range from 10ppt to 100ppb.
  crossref Kang Rong, Meizhen Zhang, Alan X. Wang 2026-07-28T21:01:09Z 置信度 0.70
• Machine Learning in Civil Engineering and Infrastructure Development
  Machine Learning in Civil Engineering and Infrastructure Development: A Practitioner's Handbook is a practitioner-oriented handbook that demonstrates, through diverse real-world examples, how civil engineers can integrate machine learning into projects while r…
  crossref 2026-05-18T14:39:18Z 置信度 0.70
• Graph Neural Networks (GNNs)
  crossref Tongyi Zhang 2026-06-27T09:44:39Z 置信度 0.70
• Front Matter
  crossref 2026-05-22T21:19:27Z 置信度 0.70
• Index
  crossref 2026-01-09T21:22:08Z 置信度 0.70
• Explainability First: Designing Trustworthy Machine Learning Models for Real-World Deployment
  crossref Mounica Achanta, Dharanidhar Vuppu 2026-04-20T20:01:37Z 置信度 0.70
• A quantitative review of automated neural search and on-device learning for tiny devices
  This paper presents the state-of-the-art review of the different approaches for Neural Architecture Search targeting resource constrained devices such as microcontrollers. As well as the implementations of On-Device learning techniques for those devices.
  crossref Danilo Pau, Prem Kumar Ambrose 2022-01-27T22:08:24Z 置信度 0.70
• Machine Learning with Quantum Computers
  crossref Ivana Nikoloska 2026-01-13T10:15:00Z 置信度 0.70
• Multimodal information fusion for financial forecasting via cross-attention and calibrated uncertainty
  crossref Josué Bustarviejo, Carlos Bousoño-Calzón 2026-01-12T17:11:04Z 置信度 0.70
• Using Error Correction Code Schemes in Dependable Machine Learning Systems
  crossref Jisheng Hu, Xiangyu Wang, Wenqi Zhang, Linhao Guo 等 2026-05-22T11:12:09Z 置信度 0.70
• Data‐Driven Decision Making for Sustainable Transportation, Quantum Machine Learning, and Collaborative Filtering
  crossref D. Manju, Logesh Ravi, Ali Wagdy Mohamed, V. Subramaniyaswamy 2026-05-22T21:19:27Z 置信度 0.70
• Learning curve ACC 2017
  crossref Tiny Nair 2017-04-28T22:46:04Z 置信度 0.70
• A quantitative review of automated neural search and on-device learning for tiny devices
  This paper presents the state-of-the-art review of the different approaches for Neural Architecture Search targeting resource constrained devices such as microcontrollers. As well as the implementations of On-Device learning techniques for those devices.
  crossref Danilo Pau, Prem Kumar Ambrose 2022-01-27T17:08:24Z 置信度 0.70
• Machine Learning Operated Approaches for Advancing Efficiency of $\text{FASnI}_{3}$ Solar Cell
  crossref Raushan Kumar, Alok Priyadarshi, Asisa Kumar Panigrahy, Alisha Priya 2026-06-08T19:49:07Z 置信度 0.70
• Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC
  Abstract A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The ‘ABCD method’ provides a reliable framework for backgro…
  crossref The CMS Collaboration 2026-08-26T06:08:32Z 置信度 0.70
• Machine Learning for Drug Discovery: A Review of Molecular Property Prediction
  The discovery and optimization of therapeutic molecules increasingly depend on computational methods capable of predicting molecular properties prior to experimental validation. Molecular property prediction encompasses a broad range of tasks, including physic…
  crossref Kumar Aryan 2026-06-29T17:10:48Z 置信度 0.70