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AAAI Spring Symposium 2022 - Machine Learning and Knowledge Engineering: Stanford University, Palo Alto, CA, USA
- Andreas Martin, Knut Hinkelmann, Hans-Georg Fill, Aurona Gerber, Doug Lenat, Reinhard Stolle, Frank van Harmelen:
Proceedings of the AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022), Stanford University, Palo Alto, California, USA, March 21-23, 2022. CEUR Workshop Proceedings 3121, CEUR-WS.org 2022 - Andreas Martin, Knut Hinkelmann:
AAAI-MAKE 2022: Machine Learning and Knowledge Engineering for Hybrid Intelligence.
Regular Papers
- Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash:
Combining Learning From Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. - Glen Smith, Qiao Zhang, Christopher J. MacLellan:
Do It Like the Doctor: How We Can Design a Model That Uses Domain Knowledge to Diagnose Pneumothorax. - Benedikt Wagner, Artur S. d'Avila Garcez:
Neural-Symbolic Reasoning Under Open-World and Closed-World Assumptions. - Agnese Chiatti, Enrico Motta, Enrico Daga:
Robots With Commonsense: Improving Object Recognition Through Size and Spatial Awareness. - Stephan Jüngling, Martin Peraic, Cheng Zhu:
Using the Strategy Design Pattern for Hybrid AI System Design. - Giorgos Filandrianos, Konstantinos Thomas, Edmund Dervakos, Giorgos Stamou:
Conceptual Edits as Counterfactual Explanations. - Markus Lochbrunner, Hans Friedrich Witschel:
Combining Machine Learning With Human Knowledge for Delivery Time Estimations. - Wolfgang Maass, Arturo Castellanos, Monica Chiarini Tremblay, Roman Lukyanenko, Veda C. Storey:
ConceptSuperimposition: Using Conceptual Modeling Method for Explainable AI. - Suk Joon Hong, Brandon Bennett, Judith Clymo, Lucía Gómez Álvarez:
KARaML: Integrating Knowledge-Based and Machine Learning Approaches to Solve the Winograd Schema Challenge. - Pouya Ghiasnezhad Omran
, Zhe Wang, Kewen Wang:
Learning Rules With Attributes and Relations in Knowledge Graphs. - Fabian Muff
A Framework for Context-Dependent Augmented Reality Applications Using Machine Learning and Ontological Reasoning. - Utkarsh Nath, Shrinu Kushagra, Yingzhen Yang:
Adjoined Networks: A Training Paradigm With Applications to Network Compression. - Ryan Prater, Emanuele Laurenzi:
A Hybrid Intelligent Approach for the Support of Higher Education Students in Literature Discovery. - Sakif Hossain, Fatema T. Johora, Jörg P. Müller, Sven Hartmann, Andreas Reinhardt:
SFMGNet: A Physics-Based Neural Network To Predict Pedestrian Trajectories. - Ashok K. Goel, Harshvardhan Sikka, Eric Gregori:
Agent Smith: Machine Teaching for Building Question Answering Agents. - Maaike H. T. de Boer, Steven Vethman, Roos M. Bakker, Ajaya Adhikari, Michiel Marcus, Joachim de Greeff, Jasper van der Waa, Tjeerd A. J. Schoonderwoerd, Ioannis Tolios, Emma M. van Zoelen, Fieke Hillerström, Bart Kamphorst:
The FATE System Iterated: Fair, Transparent and Explainable Decision Making in a Juridical Case. - Anupriya Ankolekar, David Brunner:
Hybrid AI System Delivering Highly Targeted News to Business Professionals. - Alexander Münzberg, Christian Troost, Daniel Martini, Francisco Mendoza, Rajiv Kumar Srivastava, Thomas Berger, Liv Seuring, Nils Reinosch, Thilo Streck, Ansgar Bernardi:
Machine Learning on Simulated and Real Farm Data Based on an Ontology-Controlled Data Infrastructure. - Kazuki Uehara, Wataru Uegami, Hirokazu Nosato, Masahiro Murakawa, Junya Fukuoka, Hidenori Sakanashi:
Explainable Deep Feature Embedding Using Multiple Instance Learning for Pathological Image Analysis. - Thomas Schmid, Florian Grosse:
Extracting Knowledge With Constructivist Machine Learning: Conceptual and Procedural Models. - Laura Greige, Fernando De Mesentier Silva, Meredith Trotter, Chris Lawrence, Peter Chin, Dilip Varadarajan:
Collusion Detection in Team-Based Multiplayer Games.
Short Papers
- Thanh Tran, Paulo E. Santos, David Powers:
Contrastive Visual and Language Translational Embeddings for Visual Relationship Detection. - Simone Colombo, Dimitrios Alivanistos, Michael Cochez:
Potential Energy to Improve Link Prediction With Relational Graph Neural Networks. - Aditeya Baral, Ansh Sarkar, Deeksha D, Ashwini M. Joshi:
CalBERT - Code-Mixed Adaptive Language Representations Using BERT. - Sudhir Agarwal, Lalla Mouatadid, Anu Sreepathy, Kevin Furbish, Morgen Kimbrell, Mike Gabriel:
Actionable Recommendations for Small Businesses With Hybrid AI. - Justin D. Brody, Donald Perlis:
Decision Transformers for Glut Control in the Active Logic Machine. - Maëlic Neau, Paulo E. Santos, Anne-Gwenn Bosser, Nathan Beu, Cédric Buche:
Commonsense Reasoning for Identifying and Understanding the Implicit Need of Help and Synthesizing Assistive Actions. - Achim Reiz, Birger Lantow, Kurt Sandkuhl:
SemOI2 - Building Adaptive and Cost-Effective Recognition Applications With Semantic Augmentation.
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