• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 193 matches

• 2024
• 
  Min Soo Kang, Sung Yul Park, Myung-Ae Chung, Donghun Han:
  No-Code AI - Concepts and Applications in Machine Learning, Visualization, and Cloud Platforms. WorldScientific 2024, ISBN 9789811293887, pp. 1-404
• 
  Tom Kohn:
  Secrets of Machine Learning - How It Works and What It Means for You. WorldScientific 2024, ISBN 9781800614888, pp. 1-240
• 
  Yuan Yan Tang, Lixiang Xu:
  Wavelet Theory Approach to Pattern Recognition - 3^rd Edition. Series in Machine Perception and Artificial Intelligence 90, WorldScientific 2024, ISBN 9789811284045, pp. 1-564
• 
  Zheng Rong Yang:
  Bio-Kernel Machines and Applications. WorldScientific 2024, ISBN 9789811287336, pp. 1-268
• 
  Simon Larsson, Martin Viktorelius:
  Reducing the contingency of the world: magic, oracles, and machine-learning technology. AI Soc. 39(1): 183-193 (2024)
• 
  Andrew M. Davis, Shawn Mankad, Charles J. Corbett, Elena Katok:
  OM Forum - The Best of Both Worlds: Machine Learning and Behavioral Science in Operations Management. Manuf. Serv. Oper. Manag. 26(5): 1605-1621 (2024)
• 
  A. David Wunsch:
  His Majesty's Airship: The Life and Tragic Death of the World's Largest Flying Machine - Samuel C. Gwynne (New York, NY, USA: Scribner, 2003, 299 pp.). IEEE Technol. Soc. Mag. 43(1): 14-16 (2024)
• 
  Otoya Nakakaze, István Koren, Florian Brillowski, Ralf Klamma:
  Adaptive retrofitting for industrial machines: utilizing webassembly and peer-to-peer connectivity on the edge. World Wide Web (WWW) 27(1): 7 (2024)
• 
  Yujia Wang, Haoran Yu:
  Predicting Real-World Penny Auction Durations by Integrating Game Theory and Machine Learning. AAAI 2024: 9926-9934
• 
  Brian Plancher, Sebastian Büttrich, Jeremy Ellis, Neena Goveas, Laila D. Kazimierski, Jesús Alfonso López Sotelo, Milan Lukic, Diego Mendez, Rosdiadee Nordin, Andrés Oliva Trevisan, Massimo Pavan, Manuel Roveri, Marcus Rüb, Jackline Tum, Marian Verhelst, Salah Abdeljabar, Segun Adebayo, Thomas Amberg, Halleluyah Aworinde, José Bagur, Gregg Barrett, Nabil Benamar, Bharat S. Chaudhari, Ronald Criollo, David Cuartielles, José A. Ferreira Filho, Solomon Gizaw, Evgeni Gousev, Alessandro Grande, Shawn Hymel, Peter Ing, Prashant Manandhar, Pietro Manzoni, Boris Murmann, Eric Pan, Rytis Paskauskas, Ermanno Pietrosemoli, Tales C. Pimenta, Marcelo Rovai, Marco Zennaro, Vijay Janapa Reddi:
  TinyML4D: Scaling Embedded Machine Learning Education in the Developing World. AAAI Spring Symposia 2024: 508-515
• 
  Carlos R. Cunha, André Moreira, Sílvia Coelho, Vítor Mendonça, João Pedro Gomes:
  Empowering the Teaching and Learning of Geometry in Basic Education by Combining Extended Reality and Machine Learning. WorldCIST (4) 2024: 98-109
• 
  João Pavão, Rute Bastardo, Nelson Pacheco da Rocha:
  A Scoping Review of the Use of Blockchain and Machine Learning in Medical Imaging Applications. WorldCIST (2) 2024: 107-117
• 
  Lesly Ttito Ugarte, Flavia Bernardini:
  An Overview on the Use of Machine Learning Algorithms for Identifying Anomalies in Industrial Valves. WorldCIST (1) 2024: 3-12
• 
  Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni:
  Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice. WWW 2024: 267-275
• 
  Raima Carol Appaw, Nicholas Fountain-Jones, Michael A. Charleston:
  What makes a small-world network? Leveraging machine learning for the robust prediction and classification of networks. CoRR abs/2403.13215 (2024)
• 
  Yan Meng, Di Wu, Christof Monz:
  How to Learn in a Noisy World? Self-Correcting the Real-World Data Noise on Machine Translation. CoRR abs/2407.02208 (2024)
• 
  Hannah Kerner, Snehal Chaudhari, Aninda Ghosh, Caleb Robinson, Adeel Ahmad, Eddie Choi, Nathan Jacobs, Chris Holmes, Matthias Mohr, Rahul Dodhia, Juan M. Lavista Ferres, Jennifer Marcus:
  Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation. CoRR abs/2409.16252 (2024)
• 2023
• 
  George Chapline:
  Quantum Mechanics and Bayesian Machines. WorldScientific 2023, ISBN 9789813232464, pp. 1-196
• 
  Ping-Yeh Chiang:
  Reliability of Machine Learning Models in the Real World. University of Maryland, College Park, MD, USA, 2023
• 
  Olivera Stojanovic:
  Interpretable machine learning for real-world applications. University of Osnabrück, Germany, 2023
• 
  Martin Ullrich:
  Fall Risk Prediction in Parkinson's Disease Using Machine Learning and Real-World Inertial Sensor-Based Gait Analysis (Sturzrisikovorhersage beim Parkinsonsyndrom mit Hilfe von Maschinellem Lernen und Inertialsensor-basierter Ganganalyse in der realen Welt). University of Erlangen-Nuremberg, Germany, 2023
• 
  Hongxin Wei:
  Natural robustness of machine learning in the open world. Nanyang Technological University, Singapore, 2023
• 
  Claudia V. Roberts:
  Human-machine Collaboration in Real-World Machine-Learning Applications. Princeton University, USA, 2023
• 
  Josef Jon, Ondrej Bojar:
  Breeding Machine Translations: Evolutionary approach to survive and thrive in the world of automated evaluation. ACL (1) 2023: 2191-2212
• 
  Zhuang Li, Lizhen Qu, Philip R. Cohen, Raj Tumuluri, Gholamreza Haffari:
  The Best of Both Worlds: Combining Human and Machine Translations for Multilingual Semantic Parsing with Active Learning. ACL (1) 2023: 9511-9528
• 
  Junhao Li, Ville Paananen, Sharadhi Alape Suryanarayana, Eetu Huusko, Miikka Kuutila, Mika Mäntylä, Simo Hosio:
  It is an online platform and not the real world, I don't care much: Investigating Twitter Profile Credibility With an Online Machine Learning-Based Tool. CHIIR 2023: 117-127
• 
  Thomas Smits, Ben Lee, Paul Fyfe:
  Using Multimodal Machine Learning to Distant View the Illustrated World of the Illustrated London News, 1842-1900. DH 2023
• 
  Fabian Rivas, José Varela Aldás, Cofre Nadia, Jessica S. Ortiz, Guamán Dennis, Guzmán Edwin:
  Simulation of an Automated System with Hardware in the Loop Using a Human Machine Interface (HMI) for the Process of Bottling Liquids Employing Unity 3D. WorldCIST (2) 2023: 550-557
• 
  Paula Rodriguez Diaz, Tejumade Afonja, Konstantin Klemmer, Aya Salama, Niveditha Kalavakonda, Oluwafemi Azeez, Simone Fobi:
  Proceedings of the NeurIPS 2021 Workshop on Machine Learning for the Developing World: Global Challenges. CoRR abs/2301.04007 (2023)
• 
  Zhuang Li, Lizhen Qu, Philip R. Cohen, Raj V. Tumuluri, Gholamreza Haffari:
  The Best of Both Worlds: Combining Human and Machine Translations for Multilingual Semantic Parsing with Active Learning. CoRR abs/2305.12737 (2023)

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