Tom M. Mitchell
- 1 Bareiss, R., Porter, B., and Vv'eir, C. PROTOS: An exempk~r~based learn~ mg apprentice. Tech. R.ep. A187-53, Univ. of ~!~xas at: Austin, Austin, Texas, 1988, Google Scholar
Digital Library
- 2 Bocionek, S. and Sassin, M. Dialogbased learning (DBL) fbr adaptive mterrace agents and programming-bydemonstration systems. I~ch. Rep. CMU.-CS-93-.I75, Carnegie Mellon. Univ., Pittsburgh, Pa., 19{t3, Google ScholarDigital Library
- 3 Caruana, R. and Freitag, D. Greedy attribute selection. In Proceedings o/'lhe Eh,venth. International Co~gerence on Mach:ine Learning.july i994.Google Scholar
- 4 Dent, L,, Boticario, J., McDermott, j., Mitchell, T., and Zabowski, D. A per. sonal, learmng apprentice. In Proceedings of the International.Joint Co~{fi, rence o-n. Art{ficiat Intelligence. 1992.Google Scholar
- 5 Foltz, P.W. and Dumais, T. Personab ized infbrmation delivery: .,M~ analysis of inibrmation filtering methods. Commun. A CM _35, I2 (1990), 51-60. Google ScholarDigital Library
- 6 Iloite, R, and Drummond, C. A learning apprentice. "I~ch. Rep~ Univ. of Ottawa, 1994.Google Scholar
- 7 Jouxdan, J., l)ent, I ... McI)ermott, j., Mitchell. T.,,. and Zabowski, D. InteJ:- faces that |earn: A learning apprentice fbr calendar management, Tech. Rep. (;MU-CS-91-135, Carnegie Mellon Univ,, Pittsburgh, Pa,, 1991.Google Scholar
- 8 Kay, A. Compt~ter software. Sci. Am. 25!, 3 (I 984), 53-59.Google Scholar
- 9 Kodratofl, Y. and Teucci, (.;~ I.)ISCt- PLE: An iterative approach to learning appren:tice systems. Tech, Rep. UPS-293, Laboramire de Recherche enlnfi)rmatique, U:niversite de PARIS-SUD, Paris, France, 1.986,Google Scholar
- 10 Kozierok, R, and Mac:s, P,. Intelligent groupware fbr scheduling meetings. Submitted to (.;SCW-92, 1992:.Google Scholar
- 11 Mitchell, T.M,, Mahadevan, S., and Steinberg, L, I.EAP: A Iearnmg apprentice for VLSI design. I:~ Proceedi:ngs .0/ the Ni:nth International Joint Con- .ference on. Art{'{i:cial Intelligence, 1985.:Google Scholar
- 12 Nakauchi, Y., Okada, T. and Anzai, Y. Groupware that learns, tn t-roceedi:ug~ (~}~the IEEE Pa.ctj}Tc Rim Communicario.us, Compute,:s and Sigmd Processi~g C.0.~!.fi, rence. IEEE, New York, 19~1iGoogle Scholar
- 13 Negroponte, N. The Architecture Machine: Towards a More Human Environmerit. MIT Press, Cambridge, Mass., 1970.Google Scholar
- 14 Quin.lan, .J.R. Generating .prodt~ction rules from decision trees. 1n Proceedings ~{"the hUernational Joint Conference on. A rt{fic.ial intelligen.ce. Google ScholarDigital Library
- 15 Quinlan, J.R. Induction of decision trees. Math. Learn. I, I (.I.986), 8.1- t06. Google ScholarDigital Library
- 16 RumeIhart, D.E., Hinton, G.E. and Williams. R.j. Learning internal representations by error pr.opagation. In Parallel Distributed Procesaing. M IT Press. Cambridge, Mass., 1986, p.p~ 318- 362. Google ScholarDigital Library
- 17 Russell, S. ,amatogicat and inductive reasoning. Ph.D. thesis, Computer Science Dept., 1986, Google ScholarDigital Library
- 18 Sadeh N. l.ook-ahead techniques i0r micro-opportunistic job .shop scheduling. Ph.D. thesis, Robotics I.nst., Carnegie Mellon Univ.,. Pi.ttsburg|.~., Pa. ! 99!. Google ScholarDigital Library
- 19 Salton, G, and Buckley, C. Improving retrieval peribrmance by relevance feedback. JASIS 41 (11990), 288-297.Google ScholarCross Ref
- 20 Schlimmer, J.C. Redstone: A learning apprentice of text tran.sformations for cataloging.Google Scholar
- 21 Sheth, B. and Maes, P. Evolving agents !br personalized information filtering, In Proceedings o{ the Ninth 1EEE Co~:(/'erence 0'n, Allot Application.s. IEEE, New York, 1993.Google Scholar
Index Terms
- Experience with a learning personal assistant
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