| 2008 |
|---|
| 89 | EE | Pedro Domingos,
Stanley Kok,
Daniel Lowd,
Hoifung Poon,
Matthew Richardson,
Parag Singla:
Markov Logic.
Probabilistic Inductive Logic Programming 2008: 92-117 |
| 2007 |
|---|
| 88 | | Hoifung Poon,
Pedro Domingos:
Joint Inference in Information Extraction.
AAAI 2007: 913-918 |
| 87 | EE | Stanley Kok,
Pedro Domingos:
Statistical predicate invention.
ICML 2007: 433-440 |
| 86 | EE | Daniel Lowd,
Pedro Domingos:
Recursive Random Fields.
IJCAI 2007: 950-955 |
| 85 | EE | Daniel Lowd,
Pedro Domingos:
Efficient Weight Learning for Markov Logic Networks.
PKDD 2007: 200-211 |
| 84 | EE | Pedro Domingos,
Parag Singla:
Markov Logic in Infinite Domains.
Probabilistic, Logical and Relational Learning - A Further Synthesis 2007 |
| 83 | EE | Pedro Domingos:
Toward knowledge-rich data mining.
Data Min. Knowl. Discov. 15(1): 21-28 (2007) |
| 2006 |
|---|
| 82 | | Parag Singla,
Pedro Domingos:
Memory-Efficient Inference in Relational Domains.
AAAI 2006 |
| 81 | | Hoifung Poon,
Pedro Domingos:
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies.
AAAI 2006 |
| 80 | | Pedro Domingos,
Stanley Kok,
Hoifung Poon,
Matthew Richardson,
Parag Singla:
Unifying Logical and Statistical AI.
AAAI 2006 |
| 79 | EE | Pedro Domingos:
Learning, Logic, and Probability: A Unified View.
EKAW 2006: 2 |
| 78 | EE | Pedro Domingos:
Learning, Logic, and Probability: A Unified View.
IBERAMIA-SBIA 2006: 3 |
| 77 | EE | Parag Singla,
Pedro Domingos:
Entity Resolution with Markov Logic.
ICDM 2006: 572-582 |
| 76 | EE | Pedro Domingos:
Learning, Logic, and Probability: A Unified View.
PRICAI 2006: 1 |
| 75 | EE | Matthew Richardson,
Pedro Domingos:
Markov logic networks.
Machine Learning 62(1-2): 107-136 (2006) |
| 2005 |
|---|
| 74 | | Parag Singla,
Pedro Domingos:
Discriminative Training of Markov Logic Networks.
AAAI 2005: 868-873 |
| 73 | | Pedro Domingos,
Fernando M. Silva,
Horácio C. Neto:
An Efficient and Scalable Architecture for Neural Networks with Backpropagation Learning.
FPL 2005: 89-94 |
| 72 | EE | Stanley Kok,
Pedro Domingos:
Learning the structure of Markov logic networks.
ICML 2005: 441-448 |
| 71 | EE | Daniel Lowd,
Pedro Domingos:
Naive Bayes models for probability estimation.
ICML 2005: 529-536 |
| 70 | EE | Parag Singla,
Pedro Domingos:
Collective Object Identification.
IJCAI 2005: 1636-1637 |
| 69 | EE | Parag Singla,
Pedro Domingos:
Object Identification with Attribute-Mediated Dependences.
PKDD 2005: 297-308 |
| 68 | | Michael L. Anderson,
Thomas Barkowsky,
Pauline Berry,
Douglas S. Blank,
Timothy Chklovski,
Pedro Domingos,
Marek J. Druzdzel,
Christian Freksa,
John Gersh,
Mary Hegarty,
Tze-Yun Leong,
Henry Lieberman,
Ric K. Lowe,
Susann Luperfoy,
Rada Mihalcea,
Lisa Meeden,
David P. Miller,
Tim Oates,
Robert Popp,
Daniel Shapiro,
Nathan Schurr,
Push Singh,
John Yen:
Reports on the 2005 AAAI Spring Symposium Series.
AI Magazine 26(2): 87-92 (2005) |
| 67 | EE | Steffen Staab,
Pedro Domingos,
Peter Mika,
Jennifer Golbeck,
Li Ding,
Timothy W. Finin,
Anupam Joshi,
Andrzej Nowak,
Robin R. Vallacher:
Social Networks Applied.
IEEE Intelligent Systems 20(1): 80-93 (2005) |
| 2004 |
|---|
| 66 | EE | Pedro Domingos:
Learning, Logic, and Probability: A Unified View.
ALT 2004: 53 |
| 65 | EE | Pedro Domingos:
Real-World Learning with Markov Logic Networks.
ECML 2004: 17 |
| 64 | EE | Daniel Grossman,
Pedro Domingos:
Learning Bayesian network classifiers by maximizing conditional likelihood.
ICML 2004 |
| 63 | EE | Pedro Domingos:
Learning, Logic, and Probability: A Unified View.
ILP 2004: 359 |
| 62 | EE | Nilesh N. Dalvi,
Pedro Domingos,
Mausam,
Sumit K. Sanghai,
Deepak Verma:
Adversarial classification.
KDD 2004: 99-108 |
| 61 | EE | Pedro Domingos:
Real-World Learning with Markov Logic Networks.
PKDD 2004: 17 |
| 60 | EE | Robin Dhamankar,
Yoonkyong Lee,
AnHai Doan,
Alon Y. Halevy,
Pedro Domingos:
iMAP: Discovering Complex Mappings between Database Schemas.
SIGMOD Conference 2004: 383-394 |
| 59 | | AnHai Doan,
Jayant Madhavan,
Pedro Domingos,
Alon Y. Halevy:
Ontology Matching: A Machine Learning Approach.
Handbook on Ontologies 2004: 385-404 |
| 58 | | Matthew Richardson,
Pedro Domingos:
Combining Link and Content Information in Web Search.
Web Dynamics 2004: 179-194 |
| 2003 |
|---|
| 57 | | Lise Getoor,
Ted E. Senator,
Pedro Domingos,
Christos Faloutsos:
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24 - 27, 2003
ACM 2003 |
| 56 | EE | Pedro Domingos,
Matthew Richardson:
Learning from Networks of Examples.
EPIA 2003: 5 |
| 55 | | Matthew Richardson,
Pedro Domingos:
Learning with Knowledge from Multiple Experts.
ICML 2003: 624-631 |
| 54 | | Daniel S. Weld,
Corin R. Anderson,
Pedro Domingos,
Oren Etzioni,
Krzysztof Gajos,
Tessa A. Lau,
Steven A. Wolfman:
Automatically Personalizing User Interfaces.
IJCAI 2003: 1613-1619 |
| 53 | EE | Matthew Richardson,
Rakesh Agrawal,
Pedro Domingos:
Trust Management for the Semantic Web.
International Semantic Web Conference 2003: 351-368 |
| 52 | EE | Matthew Richardson,
Pedro Domingos:
Building large knowledge bases by mass collaboration.
K-CAP 2003: 129-137 |
| 51 | EE | Tessa A. Lau,
Pedro Domingos,
Daniel S. Weld:
Learning programs from traces using version space algebra.
K-CAP 2003: 36-43 |
| 50 | | AnHai Doan,
Pedro Domingos,
Alon Y. Halevy:
Learning to Match the Schemas of Data Sources: A Multistrategy Approach.
Machine Learning 50(3): 279-301 (2003) |
| 49 | EE | Foster J. Provost,
Pedro Domingos:
Tree Induction for Probability-Based Ranking.
Machine Learning 52(3): 199-215 (2003) |
| 48 | EE | Tessa A. Lau,
Steven A. Wolfman,
Pedro Domingos,
Daniel S. Weld:
Programming by Demonstration Using Version Space Algebra.
Machine Learning 53(1-2): 111-156 (2003) |
| 47 | EE | Pedro Domingos:
Prospects and challenges for multi-relational data mining.
SIGKDD Explorations 5(1): 80-83 (2003) |
| 46 | EE | AnHai Doan,
Jayant Madhavan,
Robin Dhamankar,
Pedro Domingos,
Alon Y. Halevy:
Learning to match ontologies on the Semantic Web.
VLDB J. 12(4): 303-319 (2003) |
| 2002 |
|---|
| 45 | | Jayant Madhavan,
Philip A. Bernstein,
Pedro Domingos,
Alon Y. Halevy:
Representing and Reasoning about Mappings between Domain Models.
AAAI/IAAI 2002: 80-86 |
| 44 | EE | Corin R. Anderson,
Pedro Domingos,
Daniel S. Weld:
Relational Markov models and their application to adaptive web navigation.
KDD 2002: 143-152 |
| 43 | EE | Geoff Hulten,
Pedro Domingos:
Mining complex models from arbitrarily large databases in constant time.
KDD 2002: 525-531 |
| 42 | EE | Matthew Richardson,
Pedro Domingos:
Mining knowledge-sharing sites for viral marketing.
KDD 2002: 61-70 |
| 41 | EE | AnHai Doan,
Jayant Madhavan,
Pedro Domingos,
Alon Y. Halevy:
Learning to map between ontologies on the semantic web.
WWW 2002: 662-673 |
| 40 | EE | Pedro Domingos:
When and How to Subsample: Report on the KDD-2001 Panel.
SIGKDD Explorations 3(2): 74-75 (2002) |
| 2001 |
|---|
| 39 | EE | Pedro Domingos,
Geoff Hulten:
Catching up with the Data: Research Issues in Mining Data Streams.
DMKD 2001 |
| 38 | | Pedro Domingos,
Geoff Hulten:
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering.
ICML 2001: 106-113 |
| 37 | | Corin R. Anderson,
Pedro Domingos,
Daniel S. Weld:
Adaptive Web Navigation for Wireless Devices.
IJCAI 2001: 879-884 |
| 36 | EE | Steven A. Wolfman,
Tessa A. Lau,
Pedro Domingos,
Daniel S. Weld:
Mixed initiative interfaces for learning tasks: SMARTedit talks back.
Intelligent User Interfaces 2001: 167-174 |
| 35 | EE | Pedro Domingos,
Matthew Richardson:
Mining the network value of customers.
KDD 2001: 57-66 |
| 34 | EE | Geoff Hulten,
Laurie Spencer,
Pedro Domingos:
Mining time-changing data streams.
KDD 2001: 97-106 |
| 33 | EE | Matthew Richardson,
Pedro Domingos:
The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank.
NIPS 2001: 1441-1448 |
| 32 | EE | Pedro Domingos,
Geoff Hulten:
Learning from Infinite Data in Finite Time.
NIPS 2001: 673-680 |
| 31 | EE | AnHai Doan,
Pedro Domingos,
Alon Y. Halevy:
Reconciling Schemas of Disparate Data Sources: A Machine-Learning Approach.
SIGMOD Conference 2001: 509-520 |
| 30 | EE | Corin R. Anderson,
Pedro Domingos,
Daniel S. Weld:
Personalizing Web Sites for Mobile Users.
WWW 2001: 565-575 |
| 2000 |
|---|
| 29 | | Pedro Domingos:
A Unified Bias-Variance Decomposition for Zero-One and Squared Loss.
AAAI/IAAI 2000: 564-569 |
| 28 | EE | Pedro Domingos:
Beyond Occam's Razor: Process-Oriented Evaluation.
ECML 2000: 3 |
| 27 | | Pedro Domingos:
Bayesian Averaging of Classifiers and the Overfitting Problem.
ICML 2000: 223-230 |
| 26 | | Pedro Domingos:
A Unifeid Bias-Variance Decomposition and its Applications.
ICML 2000: 231-238 |
| 25 | | Tessa A. Lau,
Pedro Domingos,
Daniel S. Weld:
Version Space Algebra and its Application to Programming by Demonstration.
ICML 2000: 527-534 |
| 24 | EE | Pedro Domingos,
Geoff Hulten:
Mining high-speed data streams.
KDD 2000: 71-80 |
| 23 | EE | AnHai Doan,
Pedro Domingos,
Alon Y. Levy:
Learning Source Description for Data Integration.
WebDB (Informal Proceedings) 2000: 81-86 |
| 1999 |
|---|
| 22 | | Pedro Domingos:
Process-Oriented Estimation of Generalization Error.
IJCAI 1999: 714-721 |
| 21 | EE | Pedro Domingos:
MetaCost: A General Method for Making Classifiers Cost-Sensitive.
KDD 1999: 155-164 |
| 20 | | Pedro Domingos:
The Role of Occam's Razor in Knowledge Discovery.
Data Min. Knowl. Discov. 3(4): 409-425 (1999) |
| 1998 |
|---|
| 19 | | Pedro Domingos:
A Process-Oriented Heuristic for Model Selection.
ICML 1998: 127-135 |
| 18 | | Pedro Domingos:
Occam's Two Razors: The Sharp and the Blunt.
KDD 1998: 37-43 |
| 17 | EE | Pedro Domingos:
Knowledge Discovery Via Multiple Models.
Intell. Data Anal. 2(1-4): 187-202 (1998) |
| 1997 |
|---|
| 16 | | Pedro Domingos:
A Comparison of Model Averaging Methods in Foreign Exchange Prediction.
AAAI/IAAI 1997: 828 |
| 15 | | Pedro Domingos:
Learning Multiple Models without Sacrificing Comprehensibility.
AAAI/IAAI 1997: 829 |
| 14 | | Pedro Domingos:
Knowledge Acquisition form Examples Vis Multiple Models.
ICML 1997: 98-106 |
| 13 | | Pedro Domingos:
Why Does Bagging Work? A Bayesian Account and its Implications.
KDD 1997: 155-158 |
| 12 | | Pedro Domingos:
Control-Sensitive Feature Selection for Lazy Learners.
Artif. Intell. Rev. 11(1-5): 227-253 (1997) |
| 11 | | Pedro Domingos,
Michael J. Pazzani:
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss.
Machine Learning 29(2-3): 103-130 (1997) |
| 1996 |
|---|
| 10 | | Pedro Domingos:
Towards a Unified Approach to Concept Learning.
AAAI/IAAI, Vol. 2 1996: 1361 |
| 9 | | Pedro Domingos:
Fast Discovery of Simple Rules.
AAAI/IAAI, Vol. 2 1996: 1384 |
| 8 | | Pedro Domingos:
Multistrategy Learning: A Case Study.
AAAI/IAAI, Vol. 2 1996: 1385 |
| 7 | | Pedro Domingos,
Michael J. Pazzani:
Simple Bayesian Classifiers Do Not Assume Independence.
AAAI/IAAI, Vol. 2 1996: 1386 |
| 6 | | Pedro Domingos,
Michael J. Pazzani:
Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier.
ICML 1996: 105-112 |
| 5 | | Pedro Domingos:
Efficient Specific-to-General Rule Induction.
KDD 1996: 319-322 |
| 4 | | Pedro Domingos:
Linear-Time Rule Induction.
KDD 1996: 96-101 |
| 3 | | Pedro Domingos:
Unifying Instance-Based and Rule-Based Induction.
Machine Learning 24(2): 141-168 (1996) |
| 1995 |
|---|
| 2 | | Pedro Domingos:
Rule Induction and Instance-Based Learning: A Unified Approach.
IJCAI 1995: 1226-1232 |
| 1994 |
|---|
| 1 | | Pedro Domingos:
The RISE System: Conquering without Separating.
ICTAI 1994: 704-707 |
