• 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 31 matches

• 2020
• 
  Rhys Agombar, Max Lübbering, Rafet Sifa:
  A Clustering Backed Deep Learning Approach for Document Layout Analysis. CD-MAKE 2020: 423-430
• 
  Amin Anjomshoaa, Edward Curry:
  Inter-space Machine Learning in Smart Environments. CD-MAKE 2020: 535-549
• 
  Parfait Bemarisika, André Totohasina:
  An Efficient Method for Mining Informative Association Rules in Knowledge Extraction. CD-MAKE 2020: 227-247
• 
  Andrea Campagner, Federico Cabitza:
  Back to the Feature: A Neural-Symbolic Perspective on Explainable AI. CD-MAKE 2020: 39-55
• 
  Douglas Cirqueira, Dietmar Nedbal, Markus Helfert, Marija Bezbradica:
  Scenario-Based Requirements Elicitation for User-Centric Explainable AI - A Case in Fraud Detection. CD-MAKE 2020: 321-341
• 
  William Coleman, Charlie Cullen, Ming Yan, Sarah Jane Delany:
  Active Learning for Auditory Hierarchy. CD-MAKE 2020: 365-384
• 
  Padraig Corcoran:
  Function Space Pooling for Graph Convolutional Networks. CD-MAKE 2020: 473-483
• 
  Lukas Felsberger, Andrea Apollonio, Thomas Cartier-Michaud, Andreas Müller, Benjamin Todd, Dieter Kranzlmüller:
  Explainable Deep Learning for Fault Prognostics in Complex Systems: A Particle Accelerator Use-Case. CD-MAKE 2020: 139-158
• 
  Lukas Fischer, Lisa Ehrlinger, Verena Geist, Rudolf Ramler, Florian Sobieczky, Werner Zellinger, Bernhard Moser:
  Applying AI in Practice: Key Challenges and Lessons Learned. CD-MAKE 2020: 451-471
• 
  Lars Patrick Hillebrand, David Biesner, Christian Bauckhage, Rafet Sifa:
  Interpretable Topic Extraction and Word Embedding Learning Using Row-Stochastic DEDICOM. CD-MAKE 2020: 401-422
• 
  Anna Karanika, Panagiotis Oikonomou, Kostas Kolomvatsos, Christos Anagnostopoulos:
  An Ensemble Interpretable Machine Learning Scheme for Securing Data Quality at the Edge. CD-MAKE 2020: 517-534
• 
  Xiaoxiao Li, João Saúde:
  Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification. CD-MAKE 2020: 57-76
• 
  Luca Longo, Randy Goebel, Freddy Lécué, Peter Kieseberg, Andreas Holzinger:
  Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions. CD-MAKE 2020: 1-16
• 
  Jiawen Lyn, Sen Yan:
  Non-local Second-Order Attention Network for Single Image Super Resolution. CD-MAKE 2020: 267-279
• 
  Vukosi Marivate, Tshephisho Sefara:
  Improving Short Text Classification Through Global Augmentation Methods. CD-MAKE 2020: 385-399
• 
  Franz Mayr, Ramiro Visca, Sergio Yovine:
  On-the-fly Black-Box Probably Approximately Correct Checking of Recurrent Neural Networks. CD-MAKE 2020: 343-363
• 
  Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso:
  eXDiL: A Tool for Classifying and eXplaining Hospital Discharge Letters. CD-MAKE 2020: 159-172
• 
  Luke Merrick, Ankur Taly:
  The Explanation Game: Explaining Machine Learning Models Using Shapley Values. CD-MAKE 2020: 17-38
• 
  Fabrizio Nunnari, Chirag Bhuvaneshwara, Abraham Obinwanne Ezema, Daniel Sonntag:
  A Study on the Fusion of Pixels and Patient Metadata in CNN-Based Classification of Skin Lesion Images. CD-MAKE 2020: 191-208
• 
  Marco Antonio Pinto-Orellana, Hugo Lewi Hammer:
  Analysis of Optical Brain Signals Using Connectivity Graph Networks. CD-MAKE 2020: 485-497
• 
  Erika Puiutta, Eric M. S. P. Veith:
  Explainable Reinforcement Learning: A Survey. CD-MAKE 2020: 77-95
• 
  Annabelle Redelmeier, Martin Jullum, Kjersti Aas:
  Explaining Predictive Models with Mixed Features Using Shapley Values and Conditional Inference Trees. CD-MAKE 2020: 117-137
• 
  Judita Rokosná, Frantisek Babic, Ljiljana Trtica-Majnaric, Ludmila Pusztová:
  Cooperation Between Data Analysts and Medical Experts: A Case Study. CD-MAKE 2020: 173-190
• 
  Sanjay Sekar Samuel, Nik Nailah Binti Abdullah, Anil Raj:
  Interpretation of SVM Using Data Mining Technique to Extract Syllogistic Rules - Exploring the Notion of Explainable AI in Diagnosing CAD. CD-MAKE 2020: 249-266
• 
  Anna Saranti, Behnam Taraghi, Martin Ebner, Andreas Holzinger:
  Property-Based Testing for Parameter Learning of Probabilistic Graphical Models. CD-MAKE 2020: 499-515
• 
  Philipp Schmidt, Felix Bießmann:
  Calibrating Human-AI Collaboration: Impact of Risk, Ambiguity and Transparency on Algorithmic Bias. CD-MAKE 2020: 431-449
• 
  David Schneeberger, Karl Stöger, Andreas Holzinger:
  The European Legal Framework for Medical AI. CD-MAKE 2020: 209-226
• 
  Grah Simon, Thouvenot Vincent:
  A Projected Stochastic Gradient Algorithm for Estimating Shapley Value Applied in Attribute Importance. CD-MAKE 2020: 97-115
• 
  Martin Teuffenbach, Ewa Piatkowska, Paul Smith:
  Subverting Network Intrusion Detection: Crafting Adversarial Examples Accounting for Domain-Specific Constraints. CD-MAKE 2020: 301-320
• 
  Andreas Theissler, Simon Vollert, Patrick Benz, Laurentius Antonius Meerhoff, Marc Fernandes:
  ML-ModelExplorer: An Explorative Model-Agnostic Approach to Evaluate and Compare Multi-class Classifiers. CD-MAKE 2020: 281-300

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