Skip to main content
SpringerLink
Log in
Book cover

Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part IV

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Massih-Reza Amini

    1. Grenoble Alpes University, Saint Martin d’Hères, France

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Stéphane Canu

    1. INSA Rouen Normandy, Saint Etienne du Rouvray, France

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Asja Fischer

    1. Ruhr-Universität Bochum, Bochum, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Tias Guns

    1. KU Leuven, Leuven, Belgium

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  5. Petra Kralj Novak

    1. Central European University, Vienna, Austria

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  6. Grigorios Tsoumakas

    1. Aristotle University of Thessaloniki, Thessaloniki, Greece

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13716)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ECML PKDD 2022.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (38 papers)

  1. Front Matter

    Pages i-xlvi
    Download chapter PDF

  2. Reinforcement Learning

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Coupling User Preference with External Rewards to Enable Driver-centered and Resource-aware EV Charging Recommendation

      • Chengyin Li, Zheng Dong, Nathan Fisher, Dongxiao Zhu
      Pages 3-19

    3. Multi-Objective Actor-Critics for Real-Time Bidding in Display Advertising

      • Haolin Zhou, Chaoqi Yang, Xiaofeng Gao, Qiong Chen, Gongshen Liu, Guihai Chen
      Pages 20-37

    4. Batch Reinforcement Learning from Crowds

      • Guoxi Zhang, Hisashi Kashima
      Pages 38-51

    5. Oracle-SAGE: Planning Ahead in Graph-Based Deep Reinforcement Learning

      • Andrew Chester, Michael Dann, Fabio Zambetta, John Thangarajah
      Pages 52-67

    6. Reducing the Planning Horizon Through Reinforcement Learning

      • Logan Dunbar, Benjamin Rosman, Anthony G. Cohn, Matteo Leonetti
      Pages 68-83

    7. State Representation Learning for Goal-Conditioned Reinforcement Learning

      • Lorenzo Steccanella, Anders Jonsson
      Pages 84-99

    8. Bootstrap State Representation Using Style Transfer for Better Generalization in Deep Reinforcement Learning

      • Md Masudur Rahman, Yexiang Xue
      Pages 100-115

    9. Imitation Learning with Sinkhorn Distances

      • Georgios Papagiannis, Yunpeng Li
      Pages 116-131

    10. Safe Exploration Method for Reinforcement Learning Under Existence of Disturbance

      • Yoshihiro Okawa, Tomotake Sasaki, Hitoshi Yanami, Toru Namerikawa
      Pages 132-147

    11. Model Selection in Reinforcement Learning with General Function Approximations

      • Avishek Ghosh, Sayak Ray Chowdhury
      Pages 148-164

  3. Multi-agent Reinforcement Learning

    1. Front Matter

      Pages 165-165
      Download chapter PDF

    2. Heterogeneity Breaks the Game: Evaluating Cooperation-Competition with Multisets of Agents

      • Yue Zhao, José Hernández-Orallo
      Pages 167-182

    3. Constrained Multiagent Reinforcement Learning for Large Agent Population

      • Jiajing Ling, Arambam James Singh, Nguyen Duc Thien, Akshat Kumar
      Pages 183-199

    4. Reinforcement Learning for Multi-Agent Stochastic Resource Collection

      • Niklas Strauss, David Winkel, Max Berrendorf, Matthias Schubert
      Pages 200-215

    5. Team-Imitate-Synchronize for Solving Dec-POMDPs

      • Eliran Abdoo, Ronen I. Brafman, Guy Shani, Nitsan Soffair
      Pages 216-232

    6. DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems

      • Joe Eappen, Suresh Jagannathan
      Pages 233-250

    7. MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning

      • Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles Kamhoua, Evangelos E. Papalexakis et al.
      Pages 251-266

  4. Bandits and Online Learning

    1. Front Matter

      Pages 267-267
      Download chapter PDF
Back to top

Other volumes

  1. Machine Learning and Knowledge Discovery in Databases

  2. Machine Learning and Knowledge Discovery in Databases

  3. Machine Learning and Knowledge Discovery in Databases

  4. Machine Learning and Knowledge Discovery in Databases

  5. Machine Learning and Knowledge Discovery in Databases

  6. Machine Learning and Knowledge Discovery in Databases

  7. Machine Learning and Principles and Practice of Knowledge Discovery in Databases

  8. Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Keywords

About this book

The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022.

The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions.

The volumes are organized in topical sections as follows:

Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning;

Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems;

Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search;

Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning;

Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability;

Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.

Editors and Affiliations

  • Grenoble Alpes University, Saint Martin d’Hères, France

    Massih-Reza Amini

  • INSA Rouen Normandy, Saint Etienne du Rouvray, France

    Stéphane Canu

  • Ruhr-Universität Bochum, Bochum, Germany

    Asja Fischer

  • KU Leuven, Leuven, Belgium

    Tias Guns

  • Central European University, Vienna, Austria

    Petra Kralj Novak

  • Aristotle University of Thessaloniki, Thessaloniki, Greece

    Grigorios Tsoumakas

Bibliographic Information

Publish with us

Policies and ethics

Societies and partnerships

Back to top

Search

Navigation