Please delete that! Why should I?
暂无分享,去创建一个
[1] Werner Nutt,et al. Basic Description Logics , 2003, Description Logic Handbook.
[2] John K. Kruschke,et al. The Cambridge Handbook of Computational Psychology: Models of Categorization , 2008 .
[3] Stephen Muggleton,et al. Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP , 2018, Machine Learning.
[4] Anthony Jameson,et al. Making systems sensitive to the user's changing resource limitations , 1999, Knowl. Based Syst..
[5] Michael Siebers,et al. Explaining Black-Box Classifiers with ILP - Empowering LIME with Aleph to Approximate Non-linear Decisions with Relational Rules , 2018, ILP.
[6] Donald Michie,et al. Machine Learning in the Next Five Years , 1988, EWSL.
[7] Barbara Hammer,et al. Interpretable machine learning with reject option , 2018, Autom..
[8] Johannes Fürnkranz,et al. On Cognitive Preferences and the Interpretability of Rule-based Models , 2018, ArXiv.
[9] J. Potter,et al. Discourse and Social Psychology: Beyond Attitudes and Behaviour , 1987 .
[10] Martin Hilbert,et al. The World’s Technological Capacity to Store, Communicate, and Compute Information , 2011, Science.
[11] Ellen Enkel,et al. Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices , 2016 .
[12] Martin Hilbert,et al. Info Capacity| How to Measure the World’s Technological Capacity to Communicate, Store and Compute Information? Part I: Results and Scope , 2012 .
[13] Daniel D. Suthers,et al. An analysis of explanation and its implications for the design of explanation planners , 1993 .
[14] Jerry Alan Fails,et al. Interactive machine learning , 2003, IUI '03.
[15] Jure Leskovec,et al. Interpretable Decision Sets: A Joint Framework for Description and Prediction , 2016, KDD.
[16] E J Huth. The information explosion. , 1989, Bulletin of the New York Academy of Medicine.
[17] Stephen Muggleton,et al. Inverse entailment and progol , 1995, New Generation Computing.
[18] Judith Masthoff,et al. Explaining Recommendations: Design and Evaluation , 2015, Recommender Systems Handbook.
[19] Ute Schmid,et al. Automatic Generation of Analogous Problems to Help Resolving Misconceptions in an Intelligent Tutor System for Written Subtraction , 2016, ICCBR Workshops.
[20] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[21] Klaus Moser,et al. Coping with information overload in email communication: Evaluation of a training intervention , 2010, Comput. Hum. Behav..
[22] Luc De Raedt,et al. Logical and relational learning , 2008, Cognitive Technologies.
[23] T. Lombrozo. Explanatory Preferences Shape Learning and Inference , 2016, Trends in Cognitive Sciences.
[24] Andy J. Wills,et al. Models of Categorization , 2013 .
[25] Ute Schmid,et al. Inductive Programming as Approach to Comprehensible Machine Learning , 2018, DKB/KIK@KI.
[26] Stephen K. Reed,et al. Use of examples and procedures in problem solving , 1991 .
[27] Izak Benbasat,et al. Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs , 2007, J. Manag. Inf. Syst..
[28] Andreas Wendemuth,et al. Companion-Technology for Cognitive Technical Systems , 2011, KI - Künstliche Intelligenz.
[29] Johannes Fürnkranz,et al. On cognitive preferences and the plausibility of rule-based models , 2018, Machine Learning.
[30] Stephen Muggleton,et al. Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited , 2013, Machine Learning.
[31] William J. Clancey,et al. The Epistemology of a Rule-Based Expert System - A Framework for Explanation , 1981, Artif. Intell..
[32] Nava Tintarev,et al. Evaluating the effectiveness of explanations for recommender systems , 2012, User Modeling and User-Adapted Interaction.
[33] Li Chen,et al. Trust-inspiring explanation interfaces for recommender systems , 2007, Knowl. Based Syst..
[34] Huth Ej. The information explosion. , 1989, Bulletin of the New York Academy of Medicine.
[35] Elisabeth André,et al. Proceedings of the 8th international conference on Intelligent user interfaces , 2002 .
[36] Mark Sadoski,et al. Imagery and Text: A Dual Coding Theory of Reading and Writing , 2000 .
[37] Ute Schmid,et al. Inductive rule learning on the knowledge level , 2011, Cognitive Systems Research.
[38] Patrick Henry Winston,et al. Learning structural descriptions from examples , 1970 .
[39] Sumit Gulwani,et al. Inductive programming meets the real world , 2015, Commun. ACM.
[40] Robert A. Bjork,et al. Varieties of goal-directed forgetting , 1998 .
[41] D. Gentner,et al. Commonalities and differences in similarity comparisons , 1996, Memory & cognition.
[42] Andreas Wendemuth,et al. Companion-Technology for Cognitive Technical Systems , 2016, KI - Künstliche Intelligenz.
[43] Michael Siebers,et al. Requirements for a companion system to support identifying irrelevancy , 2017, 2017 International Conference on Companion Technology (ICCT).
[44] Luc De Raedt,et al. Inductive Logic Programming: Theory and Methods , 1994, J. Log. Program..
[45] Carlos Guestrin,et al. "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.
[46] Kenneth D. Forbus,et al. Companion Cognitive Systems: A Step towards Human-Level AI , 2004, AI Mag..
[47] P. Doyle,et al. Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies , 2001 .
[48] Gary Marcus,et al. Deep Learning: A Critical Appraisal , 2018, ArXiv.
[49] Ute Schmid,et al. A Human Like Incremental Decision Tree Algorithm: Combining Rule Learning, Pattern Induction, and Storing Examples , 2017, LWDA.