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• Toward a theory of machine learning
  Abstract We define a neural network as a septuple consisting of (1) a state vector, (2) an input projection, (3) an output projection, (4) a weight matrix, (5) a bias vector, (6) an activation map and (7) a loss function. We argue that the loss function can be…
  crossref Vitaly Vanchurin 2021-02-16T17:34:23Z 置信度 0.70
• Machine Learning Algorithms and IoT Sensors for Securing the Networks
  As networks and Internet of Things (IoT) devices become more complex and interconnected, robust security protocols are essential. Sophisticated cyber-attacks often outpace traditional measures, necessitating the use of modern technologies like machine learning…
  crossref Sridevi, Amrutha Kolhar 2025-04-16T11:55:06Z 置信度 0.70
• Unsupervised Learning
  crossref 2010-12-29T17:20:28Z 置信度 0.70
• Technical Note: Some Properties of Splitting Criteria
  crossref Leo Breiman 2003-02-06T17:07:14Z 置信度 0.70
• Learning Non-deterministic Finite Automata from Queries and Counterexamples
  Abstract In the recent theoretical research activity of inductive learning, in particular, of inductive inference, Angluin has introduced the model of learning called minimally adequate teacher (MAT), that is, the model of learning via membership queries and e…
  crossref T Yokomori 2023-11-02T13:23:57Z 置信度 0.70
• Deep Q-Learning
  crossref Mark Liu 2023-10-11T11:08:37Z 置信度 0.70
• Bayesian Learning For Machine Learning Investing
  More formally, every machine learning algorithm depends on 3 things which need to be able to be programmed. First, there needs to exist an experience set, sometimes called a training set. This is data that the algorithm will “learn” from. Next, there needs to …
  crossref Alexander Fleiss, Jeremy Newton 2021-11-11T02:15:11Z 置信度 0.70
• Integrating Multiple Learning Strategies in First Order Logics
  crossref A. Giordana, F. Neri, L. Saitta, M. Botta 2002-12-22T04:48:21Z 置信度 0.70
• DCLMA: Deep correlation learning with multi-modal attention for visual-audio retrieval
  crossref Jiwei Zhang, Hirotaka Hachiya 2025-07-02T11:21:54Z 置信度 0.70
• Reinforcement Learning in Sports
  crossref Kevin Ashley 2020-08-24T08:03:59Z 置信度 0.70
• Lifelong Learning
  crossref 2010-12-29T17:28:18Z 置信度 0.70
• Ridge-SVM learning models
  crossref 2014-07-15T06:09:58Z 置信度 0.70
• Tiny Approaches to the Interactive Online Lectures Under the COVID-19 Pandemic
  crossref Eiji Hiraki, Masataka Ishihara, Kazuhiro Umetani 2022-05-03T16:19:15Z 置信度 0.70
• Machine Learning and Game Playing
  crossref 2012-02-07T08:44:39Z 置信度 0.70
• Machine Learning in Systems Biology
  crossref 2011-08-29T16:57:47Z 置信度 0.70
• Machine learning
  crossref 2018-09-10T13:07:31Z 置信度 0.70
• Role of Machine Learning and Deep Learning Techniques in Detection of Disease Severity: A Survey
  The increasing number of health issues is a cause of concern for public as well as health services across the globe. However, a boom in the use of imaging techniques such as CT scans and chest radiographs has been observed for correct diagnosis. But, manual sc…
  crossref Geeta Rani, Vijaypal Singh Dhaka, Sushma Hans 2024-03-07T14:29:53Z 置信度 0.70
• Experimental Goal Regression: A Method for Learning Problem-Solving Heuristics
  crossref Bruce W. Porter, Dennis F. Kibler 2003-04-04T16:57:10Z 置信度 0.70
• Crop Yield Prediction Using Machine Learning Random Forest Algorithm
  crossref Suwarna Gothane 2024-11-04T12:07:02Z 置信度 0.70
• 2022 International Conference on Machine Learning, Control, and Robotics MLCR 2022
  crossref 2023-02-08T18:58:55Z 置信度 0.70
• Artificial Intelligence, Big Data, and Machine Learning in Industry 4.0
  Due to the digitalization of life and the fiercely competitive global market, the fourth industrial revolution was inevitable. Industry 4.0 utilizes several interconnected technologies such as artificial intelligence (AI), machine learning (ML), big data (BD) …
  crossref Georgios Lampropoulos 2023-01-20T15:44:01Z 置信度 0.70
• Machine learning techniques for agricultural image recognition
  crossref Mohammad Reza Keyvanpour, Mehrnoush Barani Shirzad 2022-05-21T07:37:19Z 置信度 0.70
• Advanced Machine Learning Models
  crossref Ricky Leung 2025-11-10T19:26:49Z 置信度 0.70
• Machine Learning Product Line Engineering: A Systematic Reuse Framework
  Machine Learning (ML) is increasingly applied across various domains, addressing tasks such as predictive analytics, anomaly detection, and decision-making. Many of these applications share similar underlying tasks, offering potential for systematic reuse. How…
  crossref Bedir Tekinerdogan 2025-06-20T05:17:42Z 置信度 0.70
• Textual Data Augmentation for Efficient Active Learning on Tiny Datasets
  crossref Husam Quteineh, Spyridon Samothrakis, Richard Sutcliffe 2020-11-29T09:51:46Z 置信度 0.70
• Tiny-transformer based multimodal biometric authentication with edge fusion and federated split learning
  crossref Khushboo Jha, Aruna Jain 2026-06-27T19:32:43Z 置信度 0.70
• Machine Learning and Deep Learning Paradigms and Case Studies
  crossref Sachit Mishra, Yash Joshi, R.S. Ponmagal 2022-02-04T11:39:17Z 置信度 0.70
• Optimizing Parameters for Machine Learning Models and Decisions in Production
  crossref 2022-09-23T22:20:53Z 置信度 0.70
• Unsupervised Learning of Multiple Motifs in Biopolymers Using Expectation Maximization
  crossref Timothy L. Bailey, Charles Elkan 2003-04-04T16:55:36Z 置信度 0.70
• Learning and Application of Different Machine Learning Methods (KNN, SVM, Decision Tree) in Different Datasets
  crossref Chaoqun Zhu 2024-11-21T19:04:04Z 置信度 0.70
• Machine Learning Versus Deep Learning Performances on the Sentiment Analysis of Product Reviews
  At this current digital era, business platforms have been drastically shifted toward online stores on internet. With the internet-based platform, customers can order goods easily using their smart phones and get delivery at their place without going to the sho…
  crossref Pumrapee Poomka, Nittaya Kerdprasop, Kittisak Kerdprasop 2021-05-27T03:08:16Z 置信度 0.70
• Application of Machine Learning and Deep Learning in Thyroid Disease Prediction
  crossref Aditi Vora, Ramchandra S. Mangrulkar, Narendra M. Shekokar, Meera Narvekar 2021-07-07T18:42:19Z 置信度 0.70
• How the Machine 'Thinks:' Understanding Opacity in Machine Learning Algorithms
  This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan…
  crossref Jenna Burrell 2015-09-16T11:01:56Z 置信度 0.70
• Machine Learning and the Philosophy of Photography
  This chapter develops a model of vision that distributes information processing, storage, and recall between ‘hardware and wetware’, demonstrating how individual perceptions can be aggregated into a larger, collective perceiving machine. The design and potenti…
  crossref Daniel Chávez Heras 2026-01-30T13:26:53Z 置信度 0.70
• Tiny-VPS: Tiny Video Panoptic Segmentation Standing on the Shoulder of Giant-VPS_supp1-3581840.pptx
  crossref Qingfeng Liu 2025-06-23T13:29:45Z 置信度 0.70
• On the Sample Complexity for Nonoverlapping Neural Networks
  crossref Michael Schmitt 2002-12-22T05:54:50Z 置信度 0.70
• Machine Learning With Python
  crossref Nikita Silaparasetty 2020-09-21T09:03:46Z 置信度 0.70
• Improved Estimates for the Accuracy of Small Disjuncts
  crossref J.R. Quinlan 2003-04-04T16:55:36Z 置信度 0.70
• Components of ML
  crossref Alexander Jung 2022-01-21T09:03:38Z 置信度 0.70
• Structural Modelling with Sparse Kernels
  crossref S.R. Gunn, J.S. Kandola 2002-12-28T13:55:48Z 置信度 0.70
• Tiny lateral displacement detection methods of image correlation matching
  crossref Xing-bo Wang 2013-03-14T21:57:49Z 置信度 0.70
• Supplemental Information 3: Machine learning models.
  crossref 2026-04-06T08:30:20Z 置信度 0.70
• Current Machine Learning
  crossref 2024-07-19T10:51:26Z 置信度 0.70
• Learning Bias
  crossref 2010-12-29T17:28:18Z 置信度 0.70
• Learning with Trees
  crossref 2020-12-22T22:34:49Z 置信度 0.70
• Learning in probabilistic models
  crossref 2012-06-19T17:06:44Z 置信度 0.70
• Classification Learning
  crossref 2010-12-29T17:42:10Z 置信度 0.70
• Module-Based Reinforcement Learning: Experiments with a Real Robot
  crossref Zsolt Kalmár, Csaba Szepesvári, András Lörincz 2002-12-22T04:48:21Z 置信度 0.70
• Google Cloud Machine Learning Engine (Cloud MLE)
  crossref Ekaba Bisong 2019-09-27T11:06:10Z 置信度 0.70
• Privacy-Preserving Transfer Learning for Community Detection in Multiple Networks: A Review.
  In order to identify communities in various networks, this study gives a thorough analysis of privacy-preserving transfer learning methods. In order to better understand the specific difficulties of implementing transfer learning in decentralized and diverse s…
  crossref Marshima Mohd Rosli 2025-05-03T06:40:36Z 置信度 0.70
• Upper and Lower Bounds on the Learning Curve for Gaussian Processes
  crossref Christopher K.I. Williams, Francesco Vivarelli 2002-12-22T05:54:50Z 置信度 0.70
• Learning curve (machine learning)
  crossref Dimitrios Toumpanakis, Andrew Murphy, Joachim Feger 2021-10-25T03:03:08Z 置信度 0.70
• Figure 3: Tiny Face detecting small faces.
  crossref 2020-12-07T05:09:32Z 置信度 0.70
• A reinforcement learning algorithm for scheduling parallel processors with identical speedup functions
  crossref Farid Ziaei, Mohammad Ranjbar 2023-07-25T13:45:47Z 置信度 0.70
• ALECSYS and the AutonoMouse: Learning to Control a Real Robot by Distributed Classifier Systems
  crossref Marco Dorigo 2003-04-04T16:55:36Z 置信度 0.70
• Genetic Reinforcement Learning for Neurocontrol Problems
  crossref Darrell Whitley, Stephen Dominic, Rajarshi Das, Charles W. Anderson 2003-04-04T16:55:36Z 置信度 0.70
• Object Detection for Embedded Systems Using Tiny Spiking Neural Networks: Filtering Noise Through Visual Attention
  crossref Hugo Bulzomi, Amélie Gruel, Jean Martinet, Takeshi Fujita 等 2023-08-22T17:35:01Z 置信度 0.70
• Correction to: Shallow Learning Versus Deep Learning in Biomedical Applications
  crossref Mithat Önder, Ümit Şentürk, Kemal Polat 2024-11-22T02:25:03Z 置信度 0.70
• Understanding Financial Impact of Machine and Deep Learning in Healthcare: An Analysis
  crossref Khurshid Ali Ganai, Bilal Ahmad Pandow 2023-02-08T14:25:10Z 置信度 0.70
• Rigorous Learning Curve Bounds from Statistical Mechanics
  crossref David Haussler, Michael Kearns, H. Sebastian Seung, Naftali Tishby 2003-11-06T11:45:40Z 置信度 0.70
• Competitive Learning
  crossref 2010-12-29T17:42:10Z 置信度 0.70
• Multi-View Representation Learning
  crossref G. Muthu Lakshmi, N. Krishnammal 2022-01-15T02:58:59Z 置信度 0.70
• Empirical Learning Using Rule Threshold Optimization for Detection of Events in Synthetic Images
  crossref David J. Montana 2003-04-04T16:55:36Z 置信度 0.70
• Implementation of Machine Learning in the Education Sector
  crossref Prayag Tiwari, Jia Qian, Qiuchi Li 2019-05-24T04:05:52Z 置信度 0.70
• Determination of Vocational Fields with Machine Learning Algorithm
  crossref Halil Ibrahim Bulbul, Ozkan Unsal 2011-02-03T16:55:42Z 置信度 0.70
• Opportunities and Challenges for Data Analytics Integrated with Machine Learning
  crossref Shabana Urooj 2025-07-29T15:15:48Z 置信度 0.70
• Machine Learning and Molecular Systems
  crossref Caroline Desgranges, Jerome Delhommelle 2023-12-13T13:35:51Z 置信度 0.70
• Smart Pollution Alert System Using Machine Learning
  This chapter proposes a novel mobile-based pollution alert system. The level of the pollutants is available in the air quality repository. This data is updated periodically by collecting the information from the sensors placed at the monitoring stations of dif…
  crossref P. Chitra, S. Abirami 2022-07-08T11:31:23Z 置信度 0.70
• Introducing Microsoft Azure Machine Learning
  crossref Roger Barga, Valentine Fontama, Wee Hyong Tok 2015-08-26T06:38:19Z 置信度 0.70
• Intraventricular haemorrhage (tiny)
  crossref Jeremy Jones 2021-10-25T03:26:23Z 置信度 0.70
• Shallow Learning vs. Deep Learning in Social Applications
  crossref Ismail A. Mageed, Ashiq H. Bhat, Jihad Alja’am 2024-10-12T18:01:28Z 置信度 0.70
• Learning with hidden variables
  crossref 2012-06-19T17:06:44Z 置信度 0.70
• Review for "Machine learning and deep learning—A review for ecologists"
  crossref 2023-02-15T16:03:19Z 置信度 0.70
• Lightning Warning Methods Based on Machine Learning and Single Station Ground Meteorological Elements
  crossref 2023-02-06T02:56:36Z 置信度 0.70
• Introduction to the Machine Learning Models
  crossref Shyamasree Ghosh, Rathi Dasgupta 2022-05-04T17:03:22Z 置信度 0.70
• Introduction to Text Mining with Machine Learning
  crossref Jan Žižka, František Dařena, Arnošt Svoboda 2019-12-17T12:05:08Z 置信度 0.70
• Using Machine Learning to Address the Complexity of Prognosis in Multimorbidity: A Systematic Approach to Develop Explainable Machine Learning Models for Prognostic Predictions
  crossref Danny Anthonimuthu 2026-03-20T10:49:41Z 置信度 0.70
• Adaptive Locality Guidance: Using Locality Guidance to Initialize the Learning of Vision Transformers on Tiny Datasets_supp1-3515076.pdf
  crossref ChengKai Lu 2025-01-24T13:32:28Z 置信度 0.70
• A novel deep learning framework for tiny person detection in complex and dynamic environments
  crossref Rakhi Nautiyal, Maroti Deshmukh 2026-06-27T15:43:24Z 置信度 0.70
• Five Tiny Doves
  crossref 2018-02-15T16:42:46Z 置信度 0.70
• Figure 8: Confusion matrix for YOLOv4-Tiny model.
  crossref 2022-08-17T04:21:23Z 置信度 0.70
• Unsupervised deep learning for semantic segmentation using laparoscopic videos: A self-detection and self-learning approach
  crossref Sina Saadati, Maryam Hashemi, Camran Nezhat 2025-10-25T05:52:16Z 置信度 0.70
• Federated Learning: Privacy-Preserving Machine Learning in Cloud Environments
  crossref Bangar Raju Cherukuri 2024-10-25T08:48:08Z 置信度 0.70
• Artificial intelligence, machine learning, and deep learning for enhancing resilience in industry 4.0, 5.0, and society 5.0
  Industry 4.0, 5.0, as well as Society 5.0, is a period of the new era’s revolutions when artificial intelligence (AI), machine learning (ML), and deep learning (DL) become the tools of improving and ensuring resilience in different spheres. The current researc…
  crossref Nitin Liladhar Rane, Ömer Kaya, Jayesh Rane 2024-10-22T06:44:05Z 置信度 0.70
• Tiny Integrated Laser and Laser Ignition Conference: Abstract Book
  crossref 2024-12-31T17:35:11Z 置信度 0.70
• Predicting Foreign Exchange EUR/USD Direction Using Machine Learning
  crossref Kevin Cedric Guyard, Michel Deriaz 2024-12-02T05:47:56Z 置信度 0.70
• Machine Learning, Infrastructures, and Their Sociomaterial Possibilities
  Abstract Machine learning hinges on various sociomaterial substrates, from computers where data is processed to infrastructures that support the networks of algorithmic experts. What happens when we place focus on these sociomaterial substrates? This chapter e…
  crossref Juan Pablo Pardo-Guerra 2024-07-18T15:54:17Z 置信度 0.70
• Artificial Intelligence and Machine Learning Algorithms
  With the recent development in technologies and integration of millions of internet of things devices, a lot of data is being generated every day (known as Big Data). This is required to improve the growth of several organizations or in applications like e-hea…
  crossref Amit Kumar Tyagi, Poonam Chahal 2022-07-08T11:31:23Z 置信度 0.70
• How to Perform Machine Learning
  crossref Arjun Panesar 2020-12-15T14:05:55Z 置信度 0.70
• A Machine Learning Approach to DNA Microarray Biclustering Analysis
  crossref S.Y. Kung, Man-Wai Mak 2006-10-11T15:41:15Z 置信度 0.70
• Prediction of Compound-protein Interactions with Machine Learning Methods
  In silico prediction of compound-protein interactions from heterogeneous biological data is critical in the process of drug development. In this chapter the authors review several supervised machine learning methods to predict unknown compound-protein interact…
  crossref Yoshihiro Yamanishi, Hisashi Kashima 2011-10-04T09:46:18Z 置信度 0.70
• Extreme learning machine based on cross entropy
  crossref Yixin Cui, Junhai Zhai, Xizhao Wang 2017-03-10T03:54:40Z 置信度 0.70
• Machine Learning Classifiers in Health Care
  crossref K. Sambath Kumar, A. Rajendran 2021-05-21T20:57:41Z 置信度 0.70
• Machine Learning of Sound and Music for Sociological Research
  Abstract Despite the significance of sound and music to social life, sociological research on these topics rarely touches upon their formal analysis, often because of disparate interests and a lack of technical tools and expertise. Recent advancements in machi…
  crossref Ke Nie 2024-06-20T16:27:54Z 置信度 0.70
• Role of Machine Learning in Promoting Sustainability
  crossref Muneza Kagzi 2022-05-19T15:50:04Z 置信度 0.70
• Feature Generation Using General Constructor Functions
  crossref Shaul Markovitch, Dan Rosenstein 2002-12-28T14:42:56Z 置信度 0.70
• A Novel Machine Learning-Based Heart Murmur Detection and Classification using Sound Feature Analysis
  An electrocardiogram (ECG) is a common method used for diagnosis of heart diseases. ECG is not sufficient to detect heart abnormalities early. Heart sound monitoring or phonocardiogram (PCG) is a non-invasive assessment that can be performed during routine exa…
  crossref Ram Sivaraman, Joe Xiao 2024-02-04T14:25:56Z 置信度 0.70
• Automated Knowledge Acquisition for Strategic Knowledge
  crossref Thomas R. Gruber 2003-04-04T16:55:36Z 置信度 0.70
• Behavioral Prediction of Cancer Using Machine Learning
  crossref Ashish Kumar, Rishit Jain 2021-11-11T12:06:15Z 置信度 0.70
• Intelligent Resource Allocation in ERP with Machine Learning
  Efficient resource allocation is a critical component of Enterprise Resource Planning (ERP) systems. Existing approaches often rely on static allocation methods that fail to adapt to dynamic business environments, leading to inefficiencies. This paper proposes…
  crossref Veeresh Dachepalli 2025-04-22T04:45:08Z 置信度 0.70