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Artificial intelligence (AI) generally and machine learning (ML) specifically demonstrate impressive practical success in many different application domains, e.g.
Chess-playing programs and the problem of complexity
Alan Newell, John C. Shaw, and Herbert A. Simon · 1958
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A model of inexact reasoning in medicine
Edward H. Shortliffe and Bruce G. Buchanan · 1975
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Learning representations by back-propagating errors
David E. Rumelhart, Geoffrey E. Hinton, and Ronald J. Williams · 1986
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30 years of adaptive neural networks: perceptron, madaline, and backpropagation
Bernard Widrow and Michael A. Lehr · 1990
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Explanations in knowledge systems: Design for explainable expert systems
William Swartout, Cecile Paris, and Johanna Moore · 1991
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Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence
John Henry Holland · 1992
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Agents that learn to explain themselves
W. Lewis Johnson · 1994
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Genetic programming as a means for programming computers by natural selection
John R. Koza · 1994
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Artificial Intelligence: A modern approach
Stuart J. Russell and Peter Norvig · 1995
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Affective Computing
Rosalind W. Picard · 1997
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A fuzzy-genetic approach to breast cancer diagnosis
Carlos A. Pena-Reyes and Moshe Sipper · 1999
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The semantic Web
Tim Berners-Lee, James Hendler, and Ora Lassila · 2001
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Semeval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Inigo Lopez-Gazpio, and Lucia Specia · 2001
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Designing fuzzy inference systems from data: An interpretability-oriented review
Serge Guillaume · 2001
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Foveated video compression with optimal rate control
Sanghoon Lee, Marios S. Pattichis, and Alan C. Bovik · 2001
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Ontology learning for the semantic web
Alexander Maedche and Steffen Staab · 2001
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Fingerprint classification using an AM-FM model
Marios S. Pattichis, George Panayi, Alan C. Bovik, and Shun-Pin Hsu · 2001
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A review of explanation methods for Bayesian networks
Carmen Lacave and Francisco J. Diez · 2002
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Foveated video quality assessment
Sanghoon Lee, Marios S. Pattichis, and Alan C. Bovik · 2002
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Online convex programming and generalized infinitesimal gradient ascent
Martin Zinkevich · 2003
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Proteome analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations
Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Brett Poulin, Roman Eisner, Zhiyong Lu, John Anvik, Cam Macdonell, and Alona Fyshe · 2004
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Evolving rule-based systems in two medical domains using genetic programming
Athanasios Tsakonas, Georgios Dounias, Jan Jantzen, Hubertus Axer, Beth Bjerregaard, and Diedrich Graf von Keyserlingk · 2004
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Fast automatic registration of images using the phase of a complex wavelet transform: application to proteome gels
Andrew M. Woodward, Jem J. Rowland, and Douglas B. Kell · 2004
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Text2onto: a framework for ontology learning and data-driven change discovery
Philipp Cimiano and Johanna Völker · 2005
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On the analysis and interpretation of inhomogeneous quadratic forms as receptive fields
Pietro Berkes and Laurenz Wiskott · 2006
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Building explainable artificial intelligence systems
Mark G. Core, H. Chad Lane, Michael Van Lent, Dave Gomboc, Steve Solomon, and Milton Rosenberg · 2006
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Visual explanation of evidence with additive classifiers
Brett Poulin, Roman Eisner, Duane Szafron, Paul Lu, Russell Greiner, David S. Wishart, Alona Fyshe, Brandon Pearcy, Cam MacDonell, and John Anvik · 2006
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The role of causality in judgment under uncertainty
Tevye R. Krynski and Joshua B. Tenenbaum · 2007
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Texture analysis and segmentation using modulation features, generative models, and weighted curve evolution
Iasonas Kokkinos, Georgios Evangelopoulos, and Petros Maragos · 2008
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ELP: Tractable Rules for OWL 2 , pages 649–664
Markus Krötzsch, Sebastian Rudolph, and Pascal Hitzler · 2008
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Toward human level machine intelligence - is it achievable? the need for a paradigm shift
Lotfi A. Zadeh · 2008
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Multiscale AM-FM methods for diabetic retinopathy lesion detection
Carla Agurto, Victor Murray, Eduardo Barriga, Sergio Murillo, Marios Pattichis, Herbert Davis, Stephen Russell, Michael Abràmoff, and Peter Soliz · 2009
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Learning deep architectures for ai
Yoshua Bengio · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Li Kai, and Fei-Fei Li · 2009
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Visualizing higher-layer features of a deep network
Dumitru Erhan, Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2009
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Guide to Latin in international law
Aaron X. Fellmeth and Maurice Horwitz · 2009
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
Honglak Lee, Roger Grosse, Rajesh Ranganath, and Andrew Y. Ng · 2009
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Causality: Models, Reasoning, and Inference (2nd Edition)
Judea Pearl · 2009
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The path to personalized medicine
Margaret A. Hamburg and Francis S. Collins · 2010
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Predictive, personalized, preventive, participatory (P4) cancer medicine
Leroy Hood and Stephen H. Friend · 2010
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Multiscale amplitude-modulation frequency-modulation (am–fm) texture analysis of ultrasound images of the intima and media layers of the carotid artery
Christos P. Loizou, Victor Murray, Marios S. Pattichis, Marios Pantziaris, and Constantinos S. Pattichis · 2010
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Multiscale amplitude-modulation frequency-modulation (am–fm) texture analysis of multiple sclerosis in brain mri images
Christos P. Loizou, Victor Murray, Marios S. Pattichis, Ioannis Seimenis, Marios Pantziaris, and Constantinos S. Pattichis · 2010
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Learning causal models of relational domains
Marc E. Maier, Brian J. Taylor, Huseyin Oktay, and David D. Jensen · 2010
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Multiscale AM-FM demodulation and image reconstruction methods with improved accuracy
Victor Murray, Paul Rodríguez, and Marios S. Pattichis · 2010
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Deconvolutional networks
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, and Rob Fergus · 2010
Cited alongside, same era.
Learning spatiotemporal graphs of human activities
William Brendel and Sinisa Todorovic · 2011
Cited alongside, same era.
Aggregating local image descriptors into compact codes
State-of-the-art and future challenges in the integration of biobank catalogues
Heimo Müller, Robert Reihs, Kurt Zatloukal, Fleur Jeanquartier, Roxana Merino-Martinez, David van Enckevort, Morris A. Swertz, and Andreas Holzinger · 2015
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Anh Nguyen, Jason Yosinski, and Jeff Clune · 2015
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Detection of diabetic retinopathy and maculopathy in eye fundus images using fuzzy image processing
Sarni Suhaila Rahim, Vasile Palade, Chrisina Jayne, Andreas Holzinger, and James Shuttleworth · 2015
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Taking the human out of the loop: A review of bayesian optimization
Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P. Adams, and Nando de Freitas · 2015
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Can we believe the dags? a comment on the relationship between causal dags and mechanisms
Odd Olai Aalen, Kjetil Røysland, Jon Michael Gran, Roger Kouyos, and Tanja Lange · 2016
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Herve Jegou, Florent Perronnin, Matthijs Douze, Jorge Sánchez, Patrick Perez, and Cordelia Schmid · 2011
Cited alongside, same era.
Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts · 2011
Cited alongside, same era.
Tree image growth analysis using instantaneous phase modulation
Janakiramanan Ramachandran, Marios S. Pattichis, Louis A. Scuderi, and Justin S. Baba · 2011
Cited alongside, same era.
Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine
Qiang Tian, Nathan D. Price, and Leroy Hood · 2011
Cited alongside, same era.
Building interpretable fuzzy models for high dimensional data analysis in cancer diagnosis
Zhenyu Wang and Vasile Palade · 2011
Cited alongside, same era.
An adaptive multiscale AM-FM texture analysis system with application to hysteroscopy imaging
Ioannis Constantinou, Marios S. Pattichis, Vasillis Tanos, Marios Neofytou, and Constantinos S. Pattichis · 2012
Cited alongside, same era.
A practical guide to training restricted boltzmann machines
Geoffrey E. Hinton · 2012
Cited alongside, same era.
Linked Disambiguated Distributional Semantic Networks , pages 56–64
Stefano Faralli, Alexander Panchenko, Chris Biemann, and Simone P. Ponzetto · 2016
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Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research
Dominic Girardi, Josef Küng, Raimund Kleiser, Michael Sonnberger, Doris Csillag, Johannes Trenkler, and Andreas Holzinger · 2016
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Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh · 2016
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Explainable artificial intelligence (XAI): Technical Report Defense Advanced Research Projects Agency DARPA-BAA-16-53
David Gunning · 2016
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Generating visual explanations
Lisa Anne Hendricks, Zeynep Akata, Marcus Rohrbach, Jeff Donahue, Bernt Schiele, and Trevor Darrell · 2016
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Interactive machine learning for health informatics: When do we need the human-in-the-loop?
Andreas Holzinger · 2016
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Towards interactive machine learning (iML): Applying ant colony algorithms to solve the traveling salesman problem with the human-in-the-loop approach
Andreas Holzinger, Markus Plass, Katharina Holzinger, Gloria Cerasela Crisan, Camelia-M. Pintea, and Vasile Palade · 2016
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Trust for the doctor-in-the-loop
Peter Kieseberg, Edgar Weippl, and Andreas Holzinger · 2016
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Building machines that learn and think like people
Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman · 2016
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The mythos of model interpretability
Zachary C. Lipton · 2016
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Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Anh Nguyen, Alexey Dosovitskiy, Jason Yosinski, Thomas Brox, and Jeff Clune · 2016
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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Attribute and-or grammar for joint parsing of human attributes, part and pose
Seyoung Park, Bruce Xiaohan Nie, and Song-Chun Zhu · 2016
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Ultradense word embeddings by orthogonal transformation
Sascha Rothe, Sebastian Ebert, and Hinrich Schütze · 2016
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Ontology-guided principal component analysis: Reaching the limits of the doctor-in-the-loop
Sandra Wartner, Dominic Girardi, Manuela Wiesinger-Widi, Johannes Trenkler, Raimund Kleiser, and Andreas Holzinger · 2016
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2016
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An adaptive annotation approach for biomedical entity and relation recognition
Seid Muhie Yimam, Chris Biemann, Ljiljana Majnaric, Šefket Šabanović, and Andreas Holzinger · 2016
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Characterization of symbolic rules embedded in deep dimlp networks: A challenge to transparency of deep learning
Guido Bologna and Yoichi Hayashi · 2017
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What does explainable ai really mean? a new conceptualization of perspectives
Derek Doran, Sarah Schulz, and Tarek R. Besold · 2017
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Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva, Brett Kuprel, Roberto A. Novoa, Justin Ko, Susan M. Swetter, Helen M. Blau, and Sebastian Thrun · 2017
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Deep learning for ontology reasoning
Patrick Hohenecker and Thomas Lukasiewicz · 2017
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Introduction to machine learning and knowledge extraction (MAKE)
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Cross-modal deep metric learning with multi-task regularization
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Proteins behaving badly. substoichiometric molecular control and amplification of the initiation and nature of amyloid fibril formation: lessons from and for blood clotting
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Interpretable and explorable approximations of black box models
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Unsupervised does not mean uninterpretable: The case for word sense induction and disambiguation
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Deeper attention to abusive user content moderation
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Elements of causal inference: foundations and learning algorithms
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Deep learning is robust to massive label noise
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Human activity recognition using recurrent neural networks
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