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Travelled to:
1 × Australia
1 × Canada
1 × Finland
1 × Germany
1 × Israel
1 × Slovenia
12 × USA
Collaborated with:
S.Basu D.Ourston M.Bilenko A.Banerjee D.L.Chen T.N.Huynh R.C.Bunescu L.Mihalkova P.Melville U.Y.Nahm S.Ramachandran J.J.Mahoney H.T.Ng B.L.Richards L.Roy J.Ghosh C.A.Thompson M.E.Califf J.M.Zelle J.B.Konvisser J.Reisinger A.Waters B.Silverthorn B.Kulis I.S.Dhillon K.V.Pasupuleti C.Krumpelman D.H.Fisher K.B.McKusick J.W.Shavlik G.G.Towell P.Nie R.Rai J.J.Li S.Khurshid M.Gligoric
Talks about:
learn (11) cluster (5) supervis (4) theori (4) semi (4) rule (4) network (3) languag (3) induct (3) refin (3)

Person: Raymond J. Mooney

DBLP DBLP: Mooney:Raymond_J=

Facilitated 1 volumes:

ML 1990Ed

Contributed to:

PADL 20112011
ICML 20102010
ICML 20082008
ICML 20072007
ICML 20052005
KDD 20052005
ICML 20042004
KDD 20042004
KDD 20032003
CIKM 20022002
ICML 20022002
KDD 20012001
ICML 19991999
ICML 19981998
ICML 19941994
KR 19921992
ML 19911991
ML 19891989
ML 19881988
DL 20002000
ESEC/FSE 20192019

Wrote 28 papers:

PADL-2011-Mooney #learning
Learning Language from Its Perceptual Context (RJM), pp. 2–4.
ICML-2010-ReisingerWSM #modelling #topic
Spherical Topic Models (JR, AW, BS, RJM), pp. 903–910.
ICML-2008-ChenM #learning
Learning to sportscast: a test of grounded language acquisition (DLC, RJM), pp. 128–135.
ICML-2008-HuynhM #learning #logic #markov #network #parametricity
Discriminative structure and parameter learning for Markov logic networks (TNH, RJM), pp. 416–423.
ICML-2007-BunescuM #learning #multi
Multiple instance learning for sparse positive bags (RCB, RJM), pp. 105–112.
ICML-2007-MihalkovaM #bottom-up #learning #logic #markov #network
Bottom-up learning of Markov logic network structure (LM, RJM), pp. 625–632.
ICML-2005-KulisBDM #approach #clustering #graph #kernel
Semi-supervised graph clustering: a kernel approach (BK, SB, ISD, RJM), pp. 457–464.
KDD-2005-BanerjeeKGBM #clustering #modelling
Model-based overlapping clustering (AB, CK, JG, SB, RJM), pp. 532–537.
ICML-2004-BilenkoBM #clustering #constraints #learning #metric
Integrating constraints and metric learning in semi-supervised clustering (MB, SB, RJM).
ICML-2004-MelvilleM #learning
Diverse ensembles for active learning (PM, RJM).
KDD-2004-BasuBM #clustering #framework #probability
A probabilistic framework for semi-supervised clustering (SB, MB, RJM), pp. 59–68.
KDD-2003-BilenkoM #adaptation #detection #metric #similarity #string #using
Adaptive duplicate detection using learnable string similarity measures (MB, RJM), pp. 39–48.
CIKM-2002-NahmM #mining
Mining soft-matching association rules (UYN, RJM), pp. 681–683.
ICML-2002-BasuBM #clustering
Semi-supervised Clustering by Seeding (SB, AB, RJM), pp. 27–34.
KDD-2001-BasuMPG #using
Evaluating the novelty of text-mined rules using lexical knowledge (SB, RJM, KVP, JG), pp. 233–238.
ICML-1999-ThompsonCM #information management #learning #natural language #parsing
Active Learning for Natural Language Parsing and Information Extraction (CAT, MEC, RJM), pp. 406–414.
ICML-1998-RamachandranM #network #refinement
Theory Refinement of Bayesian Networks with Hidden Variables (SR, RJM), pp. 454–462.
ICML-1994-MahoneyM
Comparing Methods for Refining Certainty-Factor Rule-Bases (JJM, RJM), pp. 173–180.
ICML-1994-ZelleMK #bottom-up #induction #logic programming #top-down
Combining Top-down and Bottom-up Techniques in Inductive Logic Programming (JMZ, RJM, JBK), pp. 343–351.
KR-1992-NgM #abduction #empirical #evaluation #recognition
Abductive Plan Recognition and Diagnosis: A Comprehensive Empirical Evaluation (HTN, RJM), pp. 499–508.
ML-1991-MooneyO #induction #refinement
Constructive Induction in Theory Refinement (RJM, DO), pp. 178–182.
ML-1991-OurstonM #multi
Improving Shared Rules in Multiple Category Domain Theories (DO, RJM), pp. 534–538.
ML-1991-RichardsM #first-order
First-Order Theory Revision (BLR, RJM), pp. 447–451.
ML-1989-FisherMMST #learning
Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems (DHF, KBM, RJM, JWS, GGT), pp. 169–173.
ML-1989-MooneyO #aspect-oriented #concept #induction #learning
Induction Over the Unexplained: Integrated Learning of Concepts with Both Explainable and Conventional Aspects (RJM, DO), pp. 5–7.
ML-1988-Mooney #order
Generalizing the Order of Operators in Macro-Operators (RJM), pp. 270–283.
DL-2000-MooneyR #categorisation #learning #recommendation #using
Content-based book recommending using learning for text categorization (RJM, LR), pp. 195–204.
ESEC-FSE-2019-NieRLKMG #execution #framework
A framework for writing trigger-action todo comments in executable format (PN, RR, JJL, SK, RJM, MG), pp. 385–396.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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