Machine learning paper. Mar 11, 2026 · This paper proposes a machine learning-based method...

Machine learning paper. Mar 11, 2026 · This paper proposes a machine learning-based method for detecting position falsification attacks using three feature vectors composed of selected and derived features extracted from Basic Safety Messages, in addition to a novel confidence-based Received Signal Strength Indicator feature, termed RSSIConf. The computer then performs the same task with data it hasn't encountered before. Reports substantive results on a wide range of learning methods Jan 12, 2026 · In this article, you will learn a practical, question-driven workflow for reading machine learning research papers efficiently, so you finish with answers — not fatigue. Naturally, there have been many papers published in the field. LG); Computation and Language (cs. A. Mar 16, 2026 · Online Learning and Equilibrium Computation with Ranking Feedback Mingyang Liu, Yongshan Chen, Zhiyuan Fan, Gabriele Farina, Asuman Ozdaglar, Kaiqing Zhang Subjects: Machine Learning (cs. This article presents a brief overview of machine-learning technologies, with a concrete case study from code analysis. ResearchGate 6 days ago · A machine-learning method that reasons and adapts has been developed to solve one of the most time-consuming bottlenecks in battery development. We add tiny random bits, or create extra fake examples, before the learning starts. github. Our model, the Vector Quantised-Variational AutoEncoder (VQ-VAE), differs from VAEs in two key ways: the encoder network outputs discrete, rather than continuous, codes; and the prior is Apr 22, 2025 · Abstract page for arXiv paper 2504. To advance model alignment and autonomy, we implement a new This paper investigates the use of machine learning (ML) techniques to determine optimal debt capital structures for high-growth renewable energy firms operating in complex and uncertain financing environments. From foundational deep learning Machine Learning is an international forum focusing on computational approaches to learning. For many applications Aug 24, 2016 · In machine learning, a computer first learns to perform a task by studying a training set of examples. Attention is All You Need This seminal paper introduced the Transformer model. We argue that with machine learning (ML), a new technology is at hand, where for the first time experimental economics can contribute to enabling substantial improvement of technology. Jan 5, 2022 · We summarise the findings of our award winning paper on machine learning-based methodologies for volatility targeting portfolios. Besides, the deep learning, which is part of a broader family of machine learning methods, can intelligently analyze the data on a large scale. Learning Theory (Oct 2003) Inductive Logic Programming (Aug 2003) Fusion of Domain Knowledge with Data for Decision Support (Jul 2003) Variable and Feature Selection (Mar 2003) Machine Learning Methods for Text and Images (February 2003) Eighteenth International Conference on Machine Learning (ICML2001) (December 2002) Find the latest published documents for machine learning, Related hot topics, top authors, the most cited documents, and related journals Machine learning and AI (Artificial Intelligence) are some computer science fields that have been growing rapidly during the past decade. Conducted by researchers at Jiangxi University of Chinese Medicine, the study explores the intersection of psychological traits and AI-assisted credibility assessment in Chinese populations. 0). CL); Computer Science and Game Theory (cs. Explain its evolution with examples. a) Differentiate Rote Learning, Induction, and Reinforcement Learning. This study collects data from three wells. Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and Dec 22, 2025 · Maaman is a web-based application that automatically groups similar IoT devices into a separate section using machine-learning algorithms, which makes residential Wi-Fi more secure by stopping hackers from propagating throughout the network. The journal encompasses all aspects of research and development in ML, including but not limited to data mining, computer vision, natural language processing (NLP), … View full aims & scope The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. By studying and learning from these transformative publications, we can further our understanding of AI and machine learning, driving continued innovation and progress in the field. Browse the latest papers, news, special issues, and open source software from JMLR. 14 hours ago · This research proposes a Yield-Aware Crop Selection System Leveraging Machine Learning (ML) to address this gap. Well 1 had 881 data sets for model training, and Wells 2 and 3 had 538 and 464 data sets for model testing. 3 days ago · Find the latest research papers and news in Machine Learning. Jan 9, 2023 · 🔥Highlighting the top ML papers every week. Learning Theory (Oct 2003) Inductive Logic Programming (Aug 2003) Fusion of Domain Knowledge with Data for Decision Support (Jul 2003) Variable and Feature Selection (Mar 2003) Machine Learning Methods for Text and Images (February 2003) Eighteenth International Conference on Machine Learning (ICML2001) (December 2002) In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses–cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real-world, such as stock trading, medical and healthcare systems, and software automation May 21, 2025 · 2025 is already a landmark year for machine learning research. Mar 11, 2026 · Machine Learning Authors and titles for recent submissions Tue, 17 Mar 2026 Mon, 16 Mar 2026 Fri, 13 Mar 2026 Thu, 12 Mar 2026 Wed, 11 Mar 2026 See today's new changes Total of 144 entries : 1-50 51-100 101-144 Showing up to 50 entries per page: fewer | more | all JMLR is an international forum for high-quality scholarly articles in all areas of machine learning. It emphasizes the importance of ML in system design and optimization, especially in the context of lithium batteries. Discover five breakthrough papers that are making AI systems faster, more transparent, and easier to understand – from video object tracking to revealing why transformers work so well. Provides robust support through empirical studies, theoretical analysis, or comparison to psychological phenomena. They cover foundational concepts, groundbreaking techniques, and key advancements in the field. This paper also describes the various supervised and unsupervised algorithms with their categories, which are used to solve various problems. ⚙️ OPEN ACCESS Machine Learning: Science and Technology is a multidisciplinary open access journal that bridges the application of machine learning across the sciences with advances in machine learning methods and theory as motivated by physical insights. Fully-managed cloud GPU platform offering a range of compute, storage, and networking options. This repository contains a comprehensive, continuously updated survey of essential research papers in Machine Learning (ML) and Natural Language Processing (NLP). a) Define Machine Learning. Machine learning methods enable computers to learn without being explicitly programmed and have Dec 28, 2024 · AI-Researcher automates the scientific research process, achieving high implementation success and manuscript quality through a comprehensive benchmark system. students. This paper highlights artificial intelligence and machine learning deployments in different fields enabled by future network systems. So it would be beneficial and interesting to know what the most cited papers in machine learning are. This white paper defines MLOps, describes its purpose and increasing relevance for practitioners of machine learning and artificial intelligence, and details how organizations can use MLOps to optimize their machine learning deployments and bring prototypes in Jan 1, 2025 · This paper presents the first comprehensive security analysis of machine learning workloads in serverless environments and proposes Serverless AI Shield (SAS), a multi-layered defense framework providing pre-deployment validation, runtime monitoring, and post-execution forensics. Nov 18, 2021 · Machine learning and deep learning have accomplished various astounding feats, and key research articles have resulted in technical advances used by billions of people. ML and its hybrid Mar 12, 2026 · Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more. For anyone keen to delve into the theoretical and practical aspects of machine learning, the following ten research papers are essential reads. Machine Learning and Knowledge Extraction is an international, peer-reviewed, open access, monthly journal on machine learning and applications, see our video on YouTube explaining the MAKE journal concept. Find methods information, sources, references or conduct a literature review on Mar 22, 2021 · In this paper, we have conducted a comprehensive overview of machine learning algorithms for intelligent data analysis and applications. This paper provides a comprehensive overview of adversarial attacks, defense strategies, their real-world limitations, and future research directions — with a strong focus on misclassification in high-stakes Oct 18, 2024 · A novel machine learning framework for optimizing employee promotion decisions using Gradient Boosting Machines (GBM) with a focus on CatBoost, which significantly outperforms traditional methods and other machine learning algorithms in terms of predictive accuracy, precision, and recall. Explore advancements in state of the art machine learning research in speech and natural language, privacy, computer vision, health, and more. As the field continues to evolve, it is crucial to understand the landscape of highly cited publications to identify key trends, influential authors, and significant contributions made thus far. 1. Quick breakdown of the 'Benchmark and Survey of Automated Machine Learning Frameworks' paper. However, the limitations of current Noisy Intermediate-Scale Quantum (NISQ) devices, such as noise, limited qubit availability, and circuit depth constraints, restrict the implementation of fully quantum models. This white paper defines MLOps, describes its purpose and increasing relevance for practitioners of machine learning and artificial intelligence, and details how organizations can use MLOps to optimize their machine learning deployments and bring prototypes in Aug 31, 2020 · View a PDF of the paper titled Algorithms for Solving High Dimensional PDEs: From Nonlinear Monte Carlo to Machine Learning, by Weinan E and 2 other authors White Paper—Optimize Machine Learning Through MLOps with Dell Technologies and cnvrg. Lithium batteries face temperature - related problems that limit their applications in energy storage. 6 days ago · 1. Topics we will cover include: Why purpose-first reading beats linear, start-to-finish reading. Demonstrates how to apply learning methods to solve significant application problems Apr 4, 2025 · Machine learning is a rapidly evolving field with research papers often serving as the foundation for discoveries and advancements. Design Methodological and cross sectional study applying a BERT (bidirectional encoder representations from transformers) based A unique, visual tool to help researchers and applied scientists find and explore papers relevant to their field of work. Contribute to dair-ai/ML-Papers-of-the-Week development by creating an account on GitHub. Machine Learning is an international forum focusing on computational approaches to learning. Apr 12, 2021 · Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. To address these The study examined ways to establish a DFT - machine learning framework for analyzing molecular characteristics to tune redox potential of organic electrode materials and for small - sized datasets. Jan 30, 2026 · Objectives To train and validate a machine learning model to distinguish paper mill publications from genuine cancer research articles, and to screen the cancer research literature to assess the prevalence of papers that have textual similarities to paper mill papers. Deep learning is a machine learning concept based on artificial neural networks. This paper aims to comprehensively review machine learning applications in skin cancer diagnosis, including traditional and deep learning methods, and identify research gaps. GT) [2] arXiv:2603. This linearization facilitates the use of standard linear machine learning algorithms, demonstrated through a case study on 3D scans of lemur teeth for classification, clustering, dimension reduction, and data The paper begins by highlighting the growth of machine learning (ML) in various applications due to data availability and algorithm advancements. Oct 24, 2025 · This study applies machine learning to predict the soil nutrient levels and optimize crop yield by analyzing various regression models to enhance precision agriculture, enabling data-driven fertilizer recommendations for improved sustainability and productivity. io This white paper defines MLOps, describes its purpose and increasing relevance for practitioners of machine learning and artificial intelligence, and details how organizations can use MLOps to optimize their machine learning deployments and bring prototypes in Nov 2, 2017 · Learning useful representations without supervision remains a key challenge in machine learning. Table 1 provides an overview of the existing research studies on machine learning deployments enabled by future mobile communication systems. (5M) b) Explain Data Acquisition and Feature Engineering. (5M) 2. Understand the algorithms and principles shaping modern AI. While ML foundation models, such as FeNNix-Bio1, enable quantum-accurate simulations, they remain tethered to the inherent limits of classical data generation. According to our goal, we have briefly discussed how various types of machine learning methods can be used for making solutions to various real-world issues. io Follow on Twitter @mlpapers Machine learning papers AutoML Bayesian inference Bayesian networks Causal inference Clustering Computer vision Ensemble learning Feature extraction Feature selection Generative models Graph neural networks Interpretability Missing Machine learning and Deep Learning research advances are transforming our technology. In this paper, a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore pressure. Build, train, and deploy Machine Learning models of any size and complexity. Due to its learning capabilities from data, DL technology originated from artificial neural network (ANN), has become a hot topic in the context of computing, and is widely applied in various Abstract Machine learning (ML), a subset of artificial intelligence (AI), has gained significant traction in recent years due to its ability to analyze and interpret vast amounts of data. A list of machine learning conferences that can give you access to the the newest papers out there. Feb 5, 2025 · The pyLOT library provides a Python toolkit for linearized optimal transport techniques, enabling machine learning on point clouds by embedding distributions into a Hilbert space. A machine learning - aided smartphone - based sensing system was established for detecting Hg2+ and S2–. By understanding its impact across various domains, we can appreciate its Machine Learning Authors and titles for March 2026 No updates for this time period. Here is a collection of the most important scientific study papers in machine learning. Reports substantive results on a wide range of learning methods 4 days ago · In this Collection, we publish original research and contributions across all aspects of artificial intelligence, machine learning, and precision medicine. That hides Dec 8, 2025 · This paper proposes a novel approach that leverages generative diffusion-based machine learning methods to generate high-quality BS layouts and develops a simulator tailored for BS layout design, thereby constructing a dataset for training. Nov 1, 2025 · This study benchmarks machine learning models for forecasting the impact of ground level sulfur dioxide (SO2) and ozone (O3) on wheat in Kazakhstan and confirms gradient boosting as optimal for rapid scalar predictions and lightweight CNNs as suitable for in field diagnostics on constrained hardware. '. Mar 1, 2025 · Machine learning (ML) has emerged as a prominent field of research in computer science and other related fields, thereby driving advancements in other domains of interest. Rock-Paper-Scissors with Machine Learning A command-line Java application implementing a strategy-based design with both random and machine learning algorithms for gameplay. . In this paper, we present a comprehensive view on these machine learning algorithms that can be applied to enhance the intelligence and the capabilities of an application. JMLR seeks previously unpublished papers that contain:new algorithms with empirical, theoretical, psychological, or biological justification; experimental and/or theoretical studies yielding new insight into Machine Learning papers (landing page) mlpapers Collection of open machine learning papers View on GitHub mlpapers/mlpapers. We would like to show you a description here but the site won’t allow us. The method achieves at least 75% accuracy on a large dataset, demonstrating the potential of machine learning to simulate the relationship between molecular structures and material properties. The morphology, size, crystal information, surface elemental composition, charge information, and functional groups of the three nanomaterials were characterized. 19204 [pdf, html, other] Machine Learning with Applications (MLWA) is a peer reviewed, open access journal focused on research related to machine learning. Feb 17, 2026 · The field of Machine Learning in arXiv covers papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. 6 days ago · View a PDF of the paper titled Efficient Morphology-Control Co-Design via Stackelberg Proximal Policy Optimization, by Yanning Dai and 3 other authors 14 hours ago · Abstract: Quantum machine learning has emerged as a promising approach to enhance computational efficiency by leveraging the principles of quantum computing. 6 days ago · This paper introduces Informationally Compressive Anonymization (ICA) and the VEIL architecture, a privacy-preserving ML framework that achieves strong privacy guarantees through architectural and mathematical design rather than noise injection or cryptography. Building upon the agentic, reasoning, and coding (ARC) capabilities of its predecessor, GLM-5 adopts DSA to significantly reduce training and inference costs while maintaining long-context fidelity. Abstract This conference paper examines how individual differences in empathy affect deception detection performance when machine learning tools are employed. It involves the use of data to train models, allowing them to make predictions or decisions based on new, unseen data. Methods, results, strengths/weaknesses explained in plai Nov 8, 2022 · This paper explores the deployment of a voice-based machine learning system, XYZ, designed to detect anger and verbal conflicts in complex home environments. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. (5M) CSPaper provides actionable reviews aligned to top CS conferences like NeurIPS, ICML and ICLR. How to target sections to answer your questions and retain what Machine Learning is a subfield of artificial intelligence that focuses on the development of algorithms and statistical models that enable computers to perform tasks without explicit programming. In this paper, we present a Aug 18, 2021 · Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today’s Fourth Industrial Revolution (4IR or Industry 4. (5M) b) Describe stages in Machine Learning process with neat diagram. Numerous threats, such as identity theft and the exploitation of IoT devices as botnets in DDoS assaults, might expose residential Wi-Fi due to the Feb 17, 2026 · We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. 4 days ago · This paper identifies the convergence of High-Performance Computing (HPC), Machine Learning (ML), and Quantum Computing (QC) as the definitive solution to this bottleneck. At Machine learning, especially deep learning, has shown promise in skin cancer diagnosis but still faces challenges. Reports substantive results on a wide range of learning methods applied to various learning problems. Here are the 20 most important (most-cited) scientific papers that have been published since 2014, starting with "Dropout: a simple way to prevent neural networks from overfitting". Explore the latest full-text research PDFs, articles, conference papers, preprints and more on MACHINE LEARNING. For many applications, deep Mar 14, 2026 · Machine Learning is an international forum focusing on computational approaches to learning. Abstract Adversarial Machine Learning (AML) explores how tiny, often invisible perturbations to input data can fool even state-of-the-art ML models into making wrong predictions. Apr 21, 2025 · The number of papers has been explosive, so today let’s try to summarize 5 of the most influential that have contributed to the advancement of machine learning. A lightweight triage: title + abstract + five-minute skim. Curated papers, articles, and blogs on data science & machine learning in production. Read stories and opinions from top researchers in our research community. Abstract In this paper, we investigate how technology has contributed to experimental economics in the past and illustrate how experimental economics can contribute to technological progress in the future. The system utilizes a robust classification model to perform the initial recommendation based on key soil parameters (N, P, K, pH) and climatic factors (temperature, humidity, rainfall). 1 day ago · This paper presents a novel, web-based financial architecture that combines probabilistic machine learning with a Generative Artificial Intelligence (AI) translation layer. This idea uses a simple trick — change the training examples a bit so attackers can’t read the original details. Jul 22, 2024 · Explore the top 10 groundbreaking machine learning research papers that have revolutionized AI with cutting-edge techniques and insights. Agriculture is a key sector in India, employing nearly half of the workforce, with fertilizers playing a crucial role in crop Paper Preview Abstract In this paper, we apply machine learning methods to study phase transitions in certain statistical mechanical models on the two dimensional lattices, whose transitions involve non-local or topological properties, including site and bond percolations, the XY model and the generalized XY model. In the evolving landscape of human resource management, making informed promotion decisions is crucial for Jul 18, 2025 · This paper examines methods to secure machine learning inference (ML inference) so that sensitive data remains private and proprietary models are protected during remote processing. Jan 30, 2026 · Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more. Jul 23, 2024 · The impact of these top 10 machine learning research papers is undeniable, and their contributions to the field are significant. Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. This paper presents a comprehensive survey of relevant research on machine learning applied in landslides prevention, mainly focusing on (1) landslides detection based on images, (2) landslides susceptibility assessment, and (3) the development of landslide warning systems. Traditional methods in base station (BS) layout design often rely on manual tuning or heuristic optimization, which might lead to computational Jan 7, 2025 · AI-powered analysis of 'Machine learning and Shapley Additive exPlanations to predict metastasis of lymph nodes posterior to the recurrent laryngeal nerve in cN0 papillary thyroid carcinoma. 5}$: a Vision-Language-Action Model with Open-World Generalization Creating accurate citations in APA has never been easier! Automatically cite a book in APA by using Citation Machine's free citation generator. Mar 1, 2022 · AI Quick Summary This paper introduces a novel machine learning method for predicting material properties, exemplified by polymer compatibility. In this paper, we propose a simple yet powerful generative model that learns such discrete representations. This paper explores the fundamental concepts, methodologies, applications, challenges, and future trends of machine learning. 16054: $π_ {0. Dec 8, 2024 · Foundational machine learning papers that offer critical insights for both beginners and experts. Our collection features hundreds of meticulously curated academic papers, organized by categories to help researchers, students, and practitioners navigate the vast landscape of modern AI research. It highlights the challenges and necessary steps for successful real-world deployment, emphasizing the importance of recognizing emotions to manage anger, based on a 4-month trial in 6 homes. This study benchmarks machine learning models for forecasting the impact of ground level Protect Your Data: Machine Learning That Keeps Secrets Safe When companies train smart systems in the cloud your private info can slip out, even if you only share the final model. Drawing on a simulated panel dataset that mirrors firm scale, growth dynamics, project risk profiles, credit quality, and macroeconomic conditions, the study applies and compares three Mar 12, 2026 · Your All-in-One Learning Portal: GeeksforGeeks is a comprehensive educational platform that empowers learners across domains-spanning computer science and programming, school education, upskilling, commerce, software tools, competitive exams, and more. Feb 24, 2026 · Nature Machine Intelligence is an online-only journal publishing research and perspectives from the fast-moving fields of artificial intelligence, machine learning and robotics. The research in this sector is advancing at a breakneck pace and assisting you to keep up. 10 Must Read Machine Mar 12, 2026 · Machine learning is the ability of a machine to improve its performance based on previous results. Curated collection of Data Science, Machine Learning and Deep Learning papers, reviews and articles that are on must read list. This paper portrays the various application areas of machine learning, along with its advantages and drawbacks. Explore a comprehensive Machine Learning question paper featuring key concepts, practical exercises, and theoretical questions for B. kker dkqe zgedpraw xzizah fhknj vevgf hmv daonokr wnd itzmd