Interacting meaningfully with machine learning systems: Three experiments

[1]  Xiaojin Zhu,et al.  Semi-Supervised Learning , 2010, Encyclopedia of Machine Learning.

[2]  Desney S. Tan,et al.  CueFlik: interactive concept learning in image search , 2008, CHI.

[3]  Deborah L. McGuinness,et al.  Toward establishing trust in adaptive agents , 2008, IUI '08.

[4]  Joe Tullio,et al.  How it works: a field study of non-technical users interacting with an intelligent system , 2007, CHI.

[5]  Thomas G. Dietterich,et al.  Toward harnessing user feedback for machine learning , 2007, IUI '07.

[6]  Ting Yu.  Incorporating prior domain knowledge into inductive machine learning : its implementation in contemporary capital markets , 2007 .

[7]  Alexander Zien,et al.  Semi-Supervised Learning , 2006 .

[8]  Desney S. Tan,et al.  CueTIP: a mixed-initiative interface for correcting handwriting errors , 2006, UIST.

[9]  Paul A. Viola,et al.  Corrective feedback and persistent learning for information extraction , 2006, Artif. Intell..

[10]  Tom M. Mitchell,et al.  Text clustering with extended user feedback , 2006, SIGIR.

[11]  Duane Szafron,et al.  Visual Explanation of Evidence with Additive Classifiers , 2006, AAAI.

[12]  Mark Dredze,et al.  Activity-Centric Email: A Machine Learning Approach , 2006, AAAI.

[13]  Brad A. Myers,et al.  Answering why and why not questions in user interfaces , 2006, CHI.

[14]  Thomas G. Dietterich,et al.  A hybrid learning system for recognizing user tasks from desktop activities and email messages , 2006, IUI '06.

[15]  Vittorio Castelli,et al.  Augmentation-based learning: combining observations and user edits for programming-by-demonstration , 2006, IUI '06.

[16]  Mark Dredze,et al.  Automatically classifying emails into activities , 2006, IUI '06.

[17]  Li Chen,et al.  Trust building with explanation interfaces , 2006, IUI '06.

[18]  Margaret M. Burnett,et al.  Garbage in, garbage out? An empirical look at oracle mistakes by end-user programmers , 2005, 2005 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC'05).

[19]  Henry Lieberman,et al.  Providing Expert Advice by Analogy for On-Line Help , 2005, Web Intelligence.

[20]  Thomas G. Dietterich,et al.  Learning from Sparse Data by Exploiting Monotonicity Constraints , 2005, UAI.

[21]  Barry Smyth,et al.  Experiments in dynamic critiquing , 2005, IUI.

[22]  Yolanda Gil,et al.  User interfaces with semi-formal representations: a study of designing argumentation structures , 2005, IUI '05.

[23]  Daniel Billsus,et al.  Improving proactive information systems , 2005, IUI '05.

[24]  Jim Blythe,et al.  Task learning by instruction in tailor , 2005, IUI.

[25]  Jude W. Shavlik,et al.  Creating Advice-Taking Reinforcement Learners , 1998, Machine Learning.

[26]  Maria-Florina Balcan,et al.  Co-Training and Expansion: Towards Bridging Theory and Practice , 2004, NIPS.

[27]  Martin Mozina,et al.  Nomograms for Visualization of Naive Bayesian Classifier , 2004, PKDD.

[28]  Yiming Yang,et al.  The Enron Corpus: A New Dataset for Email Classi(cid:12)cation Research , 2004 .

[29]  Pedro M. Domingos,et al.  Adversarial classification , 2004, KDD.

[30]  Philip S. Yu,et al.  Text Classification by Labeling Words , 2004, AAAI.

[31]  Ivan Bratko,et al.  Trading Accuracy for Simplicity in Decision Trees , 1994, Machine Learning.

[32]  Thomas D. Nielsen,et al.  Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains , 2003, J. Mach. Learn. Res..

[33]  Peter Haddawy,et al.  Preference Elicitation via Theory Refinement , 2003, J. Mach. Learn. Res..

[34]  Jerry Alan Fails,et al.  Interactive machine learning , 2003, IUI '03.

[35]  Philip T. Cox,et al.  Human Centric Computing Languages and Environments , 2003 .

[36]  M. Woodbury.  Information access , 2003 .

[37]  Alan F. Blackwell,et al.  First steps in programming: a rationale for attention investment models , 2002, Proceedings IEEE 2002 Symposia on Human Centric Computing Languages and Environments.

[38]  Judy Kay,et al.  IEMS - The Intelligent Email Sorter , 2002, ICML.

[39]  Jian Su,et al.  Named Entity Recognition using an HMM-based Chunk Tagger , 2002, ACL.

[40]  Carmen Lacave,et al.  A review of explanation methods for Bayesian networks , 2002, The Knowledge Engineering Review.

[41]  Judy Kay,et al.  An intelligent interface for sorting electronic mail , 2002, IUI '02.

[42]  Urszula Chajewska,et al.  Explaining Predictions in Bayesian Networks and Influence Diagrams , 2002 .

[43]  Glenn Fung,et al.  Knowledge-Based Support Vector Machine Classifiers , 2002, NIPS.

[44]  Stan Matwin,et al.  Email classification with co-training , 2011, CASCON.

[45]  Daphne Koller,et al.  Support Vector Machine Active Learning with Applications to Text Classification , 2000, J. Mach. Learn. Res..

[46]  Ian H. Witten,et al.  Interactive machine learning: letting users build classifiers , 2002, Int. J. Hum. Comput. Stud..

[47]  H. Lieberman.  Your Wish is My Command: Programming By Example , 2001 .

[48]  Henry Lieberman,et al.  Your Wish is My Command , 2001, The Morgan Kaufmann series in interactive technologies.

[49]  John Riedl,et al.  Explaining collaborative filtering recommendations , 2000, CSCW '00.

[50]  Ian Witten,et al.  Data Mining , 2000 .

[51]  Christopher Meek,et al.  Challenges of the Email Domain for Text Classification , 2000, ICML.

[52]  Jeffrey O. Kephart,et al.  Incremental Learning in SwiftFile , 2000, ICML.

[53]  Michael J. Pazzani,et al.  Representation of electronic mail filtering profiles: a user study , 2000, IUI '00.

[54]  Brad A. Myers,et al.  Getting more out of programming-by-demonstration , 1999, CHI '99.

[55]  Eric Horvitz,et al.  Principles of mixed-initiative user interfaces , 1999, CHI '99.

[56]  Jeffrey O. Kephart,et al.  MailCat: an intelligent assistant for organizing e-mail , 1999, AGENTS '99.

[57]  Thomas Richardson,et al.  Interpretable Boosted Naïve Bayes Classification , 1998, KDD.

[58]  Avrim Blum,et al.  The Bottleneck , 2021, Monopsony Capitalism.

[59]  Visualizing the Simple Bayesian Classi er , 1997 .

[60]  Thomas G. Dietterich.  What is machine learning? , 2020, Archives of Disease in Childhood.

[61]  William W. Cohen.  Learning Rules that Classify E-Mail , 1996 .

[62]  Mark Craven,et al.  Extracting comprehensible models from trained neural networks , 1996 .

[63]  Christine Decaestecker,et al.  Multiple-Knowledge Representation in Concept Learning , 1995, ECML.

[64]  Christine Decaestecker,et al.  Multiple-knowledge representations in concept learning , 1995 .

[65]  David A. Cohn,et al.  Active Learning with Statistical Models , 1996, NIPS.

[66]  Jude W. Shavlik,et al.  Knowledge-Based Artificial Neural Networks , 1994, Artif. Intell..

[67]  W. Lewis Johnson,et al.  Agents that Learn to Explain Themselves , 1994, AAAI.

[68]  Marc Rettig,et al.  Prototyping for tiny fingers , 1994, CACM.

[69]  Igor Kononenko,et al.  Inductive and Bayesian learning in medical diagnosis , 1993, Appl. Artif. Intell..

[70]  Henry Lieberman,et al.  Watch what I do: programming by demonstration , 1993 .

[71]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[72]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[73]  David J. C. MacKay,et al.  Information-Based Objective Functions for Active Data Selection , 1992, Neural Computation.

[74]  William B. Thompson,et al.  Reconstructive Expert System Explanation , 1992, Artif. Intell..

[75]  Henri Jacques Suermondt,et al.  Explanation in Bayesian belief networks , 1992 .

[76]  Stuart J. Russell.  Prior knowledge and autonomous learning , 1991, Robotics Auton. Syst..

[77]  L. N. Kanal,et al.  Uncertainty in Artificial Intelligence 5 , 1990 .

[78]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[79]  William R. Swartout,et al.  XPLAIN: A System for Creating and Explaining Expert Consulting Programs , 1983, Artif. Intell..

[80]  William J. Clancey,et al.  The Epistemology of a Rule-Based Expert System - A Framework for Explanation , 1981, Artif. Intell..

[81]  David R. L. Worthington,et al.  Assessment of agreement among several raters formulating multiple diagnoses. , 1981, Journal of psychiatric research.

[82]  Martin F. Porter,et al.  An algorithm for suffix stripping , 1997, Program.

[83]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[84]  Peter Secretan.  Learning , 1965, Mental Health.

[85]  P. Jaccard,et al.  Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .