【IJCAI 2018】30大 Tutorial,人工智能百花齐放

【导读】当地时间 7 月 13 - 19 日,备受关注的 AI 顶级国际会议 IJCAI 在瑞典斯德哥尔摩举行。在这次会议上,人工智能和机器学习领域的研究者为我们呈现了这一领域的研究前沿,其中包括:约束学习Constraint Learning生成对抗网络(GAN)博弈论AI伦理 等等,呈现出很强的多样性;与此同时,一些资深研究者也带来了一些极具看点和启发价值的演讲和教程,其中包括:Bengio《基于深度学习的人工智能 Deep Learning for AI》中科院自动化所王飞跃《基于模糊逻辑的可解释性深度学习》等等。



IJCAI-ECAI 2018Accepted Tutorials and Schedule


以下是专知对下面Tutorials 的简单介绍:


  • T01. 对抗机器学习

    Adversarial Machine Learning
    Battista Biggio and Fabio Roli

  • 链接:

  • https://www.pluribus-one.it/sec-ml/wild-patterns/


  • T02. 使用Google-AIY树莓派套件的设计马拉松

    “AI forSocial Good” Design Hackathon Using Google-AIY Kits
    Tara Chklovski and Yolanda Gil

  • 链接:

  • http://iridescentlearning.org/ai-curriculum-hackathon-ijcai-2018/


  • T03. 程序性社会介入

    Algorithmic Social Intervention

    Bryan Wilder and Yevgeniy Vorobeychik

  • 链接:

  • http://teamcore.usc.edu/people/bryanwilder/ijcai-algorithmic-social-intervention.htm


  • T04. 人工智能与法律

    ArtificialIntelligence and the Law
    Adam Wyner

  • 链接:

  • http://www.ijcai-18.org/wp-content/uploads/2018/05/T04-AI-and-the-Law-IJCAI-ECAI-18.pdf


  • T05. 机器学习助力优化算法

    BoostingOptimization via Machine Learning
    Michele Lombardi and Michela Milano

  • 链接:

  • https://sites.google.com/view/boostingopt2018/


  • T06. 计算性社会选择及人工智能的道德准则 

    Computational Social Choice and Moral Artificial Intelligence

        Vincent Conitzer

  • 链接:

  • https://users.cs.duke.edu/~conitzer/IJCAI18comsoctutorial.html


  • T07.深度生成模型 

    DeepGenerative Models
    Aditya Grover and Stefano Ermon

  • 链接:

  • https://ermongroup.github.io/generative-models/


  • T08. 基于深度学习的人工智能

    DeepLearning for AI
    Yoshua Bengio

  • 链接:

  • http://www.iro.umontreal.ca/~bengioy/talks/IJCAI2018-DLtutorial.html


  • T09. 可废止的描述逻辑

    Defeasible Description Logics
    Ivan Varzinczak

       描述逻辑(description logic)是一種用于知识表示的逻辑语言和以其为对象的推理方法,主要用于描述概念分类及其概念之间的关系。 描述逻辑方法多数被用到涉及知识分类的应用领域,如数字图书馆和面向万维网的信息处理。 描述逻辑是当前语义网发展中本体的理论基础。

  • 链接:

  • http://ijv.ovh/ijcai2018-tutorial/


  • T10. 梦想机器

    Imagination Machines

        提出利用人工智能处理一些现象中的场景数据
        Sridhar Mahadevan

  • 链接:https://people.cs.umass.edu/~mahadeva/IJCAI_2018_Tutorial/Welcome.html


  • T11. 多赢选择:应用,原理,算法及演化

    Multiwinner Elections: Applications, Axioms, Algorithms, and Generalizations
    Piotr Faliszewski, Piotr Skowron, and Nimrod Talmon

  • 链接:

  • http://home.agh.edu.pl/~faliszew/ijcai-ecai18/


  • T12. 人工智能生成音乐

    Musical Metacreation: AI for Generative Music
    Philippe Paquier

  • 链接:

  • http://musicalmetacreation.org/musical-metacreation-tutorial-ijcai-2018/


  • T13. 有约束的神经符号学习和推理

    Neural-symbolic Learning and Reasoning with Constraints
    Luis Lamb, Marco Gori, Artur Garcez, Luciano Serafini, and Michael Spranger

  • 链接:

  • http://www.neural-symbolic.org/


  • T15. 基于本体的数据介入:理论和实践

    Ontology-based Data Access: Theory and Practice
    Roman Kontchakov and Guohui Xiao

  • 链接:

  • http://ontop.inf.unibz.it/ijcai-2018-tutorial/


  • T16. 预测人的决策过程:从预测到行动

    Predicting Human Decision-Making: From Prediction to Action
    Ariel Rosenfeld and Sarit Kraus

  • 链接:

  • /https://sites.google.com/view/predicting-human-dm


  • T17. 知识编辑最新进展

    Recent Advances in Knowledge Compilation
    Adnan Darwiche and Pierre Marquis

  • 链接:

  • http://beyondnp.org/tutorial18/


  • T18. 启发式搜索的最新研究方向

    Recent Directions in Heuristic Search
    Ariel Felner, Daniel Harabor, Sven Koenig and Nathan Sturtevant

  • 链接:

  • https://movingai.com/IJCAI18-HS/


  • T19. 可扩展离散集成和取样:基础和挑战

    Scaling Discrete Integration and Sampling: Foundations and Challenges
    Supratik Chakraborty and Kuldeep S. Meel

  • 链接:

  • http://www.comp.nus.edu.sg/~meel/Tutorials/ijcai18.html


  • T20. 维基百科在文本分析和检索中所起的作用

    The Role of Wikipedia in Text Analysis and Retrieval
    Marius Pasca

  • 链接:

  • http://www.ijcai-18.org/wp-content/uploads/2018/05/T20-Wikipedia-Text-Analysis-Retrieval-IJCAI-ECAI-18.pdf


  • T21. 基于模糊逻辑的可解释性深度学习

    Toward Interpretable Deep Learning via Fuzzy Logic
    Lixin Fan, Chee Seng Chan, and Fei-Yue Wang

  • 链接:

  • http://web.fsktm.um.edu.my/~cschan/ijcai2018


  • T22. 验证基于主体的自治系统

    Verifying Agent-Based Autonomous Systems
    Louise Dennis and Michael Fisher

  • 链接:

  • http://cgi.csc.liv.ac.uk/~lad/vabas/


QUARTER-DAYTUTORIALS


  • T23. 当论证遇上计算性社会选择

    Argumentation Meets Computational Social Choice: A Tutorial
    Dorothea Baumeister, Daniel Neugebauer, and Jörg Rothe

  • 链接:

  • https://ccc.cs.uni-duesseldorf.de/~rothe/IJCAI-2018-Tutorial-Argumentation-Meets-COMSOC


  • T24. 约束学习

    Constraint Learning
    Luc De Raedt, Andrea Passerini, and Stefano Teso

  • 链接:

  • https://dtai.cs.kuleuven.be/events/tutorial-constraint-learning-ijcai18


  • T25. 声明式空间推理:教程,方法与应用

    Declarative Spatial Reasoning: Theory, Methods, Applications
    Mehul Blatt and Carl Schultz

  • 链接:

  • http://hcc.uni-bremen.de/spatial-reasoning/


  • T26. 社交网络中的扩散机制设计

    Diffusion Mechanism Design in Social Networks
    Dengji Zhao

  • 链接:

  • http://dengji-zhao.net/ijcaiecai18.html


  • T27. 人工智能中的认知推理

    Epistemic Reasoning in AI
    François Schwarzentruber

  • 链接:

  • http://people.irisa.fr/Francois.Schwarzentruber/ijcai2018_tutorial/


  • T28. 基于博弈论和机器学习的安全分析

    GameTheory and Machine Learning for Security
    Fei Fang

  • 链接:

  • https://feifang.info/ijcai-2018-tutorial/


  • T29. 数据科学中的博弈论:获取真实的信息

    Game Theory to Data Science: Eliciting Truthful Information
    Boi Faltings and Goran Radanovic

  • 链接:

  • https://lia.epfl.ch/~faltings/ijcai2018_tutorial_web/


  • T30. 知道正确而不能做错事的机器:机器伦理的理论和实践

    Machines that Know Right and Can Not Do Wrong: The Theory and Practice of Machine Ethics
    Louise Dennis and Marija Slavkovik

  • 链接:

  • http://slavkovik.com/ijcaitutorial.html


链接:

https://www.ijcai-18.org/tutorials/


请关注专知公众号(扫一扫最下面专知二维码,或者点击上方蓝色专知),

  • 后台回复“DLAI18” 就可以获取Bengio 173页 基于深度学习的人工智能 Deep Learning for AI PPT下载链接~ 

  • 后台回复“AML18” 就可以获取Bengio 145页 对抗机器学习 Adversarial Machine Learning PPT下载链接~ 


以上就是全部的tutorial,选取Bengio《对抗机器学习 Adversarial Machine Learning》的有意思的ppt分享给大家。



-END-

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