PARADIGMS FOR MACHINE LEARNING - INTRODUCTION

被引：22
|
作者：
CARBONELL, JG
机构：
来源：
ARTIFICIAL INTELLIGENCE | 1989年 / 40卷 / 1-3期
关键词：
D O I：
10.1016/0004-3702(89)90045-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
引用
收藏
页码：1 / 9
页数：9
相关论文
共 50 条
  • [21] An introduction to quantum machine learning
    Schuld, Maria
    Sinayskiy, Ilya
    Petruccione, Francesco
    CONTEMPORARY PHYSICS, 2015, 56 (02) : 172 - 185
  • [22] Machine Learning: A Concise Introduction
    Vardeman, Stephen B.
    INTERNATIONAL STATISTICAL REVIEW, 2020, 88 (02) : 515 - 516
  • [23] Introduction: AL and Machine Learning
    Bilow, Steven Craig
    SMPTE Motion Imaging Journal, 2020, 129 (02): : 14 - 15
  • [24] Introduction to Machine Learning with Robots and Playful Learning
    Olari, Viktoriya
    Cvejoski, Kostadin
    Eide, Oyvind
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 15630 - 15639
  • [25] Machine learning and deep learning: Introduction and applications
    Nakashima T.
    Zairyo, 2020, 9 (633-639): : 633 - 639
  • [26] Machine Learning Paradigms Advances in Deep Learning-based Technological Applications
    Szczerbicki, Edward
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2021, 15 (01): : 9 - 9
  • [27] Dependability of Alternative Computing Paradigms for Machine Learning: hype or hope?
    Bolchini, Cristiana
    Bosio, Alberto
    Cassano, Luca
    Deveautour, Bastien
    Di Natale, Giorgio
    Miele, Antonio
    O'Connor, Ian
    Vatajelu, Ioana
    2022 25TH INTERNATIONAL SYMPOSIUM ON DESIGN AND DIAGNOSTICS OF ELECTRONIC CIRCUITS AND SYSTEMS (DDECS), 2022, : 7 - 13
  • [28] MACHINE LEARNING PARADIGMS FOR NEXT-GENERATION WIRELESS NETWORKS
    Jiang, Chunxiao
    Zhang, Haijun
    Ren, Yong
    Han, Zhu
    Chen, Kwang-Cheng
    Hanzo, Lajos
    IEEE WIRELESS COMMUNICATIONS, 2017, 24 (02) : 98 - 105
  • [29] Taxonomy of machine learning paradigms: A data-centric perspective
    Emmert-Streib, Frank
    Dehmer, Matthias
    WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2022, 12 (05)
  • [30] Analyzing Road Accident Data using Machine Learning Paradigms
    Nandurge, Priyanka A.
    Dharwadkar, Nagaraj V.
    2017 INTERNATIONAL CONFERENCE ON I-SMAC (IOT IN SOCIAL, MOBILE, ANALYTICS AND CLOUD) (I-SMAC), 2017, : 604 - 610
12345