BibSLEIGH — Raymond_J

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: Mooney:Raymond_J=

Facilitated 1 volumes:

Contributed to:

2011

2010

2008

2007

2005

2004

2003

2002

2001

1999

1998

1994

1992

1991

1989

1988

2000

2019

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.