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ORCIDPeter J. Haas
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- affiliation: University of Massachusetts, Amherst, MA, USA
- affiliation (former): Thomas J. Watson Research Center, Yorktown Heights, USA
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2020 – today
- 2024
[j46]Anh L. Mai, Pengyu Wang, Azza Abouzied, Matteo Brucato, Peter J. Haas, Alexandra Meliou:
Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization. Proc. VLDB Endow. 17(5): 1146-1158 (2024)- 2023
- [j45]Brian Hentschel
, Peter J. Haas, Yuanyuan Tian:
Exact PPS sampling with bounded sample size. Inf. Process. Lett. 182: 106382 (2023) - [j44]Wang Cen, Peter J. Haas:
NIM: Generative Neural Networks for Automated Modeling and Generation of Simulation Inputs. ACM Trans. Model. Comput. Simul. 33(3): 10:1-10:26 (2023) - [c73]Francisco Castro, Sahitya Raipura, Heather M. Conboy, Peter J. Haas, Leon J. Osterweil, Ivon Arroyo:
Piloting an Interactive Ethics and Responsible Computing Learning Environment in Undergraduate CS Courses. SIGCSE (1) 2023: 659-665 - [c72]Pracheta Amaranath, Peter J. Haas, David D. Jensen, Sam Witty:
Causal Dynamic Bayesian Networks for Simulation Metamodeling. WSC 2023: 746-757 - [c71]Wang Cen, Peter J. Haas:
Efficient Hybrid Simulation Optimization via Graph Neural Network Metamodeling. WSC 2023: 3541-3552 - [i11]Anh L. Mai, Pengyu Wang, Azza Abouzied, Matteo Brucato, Peter J. Haas, Alexandra Meliou:
Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization. CoRR abs/2307.02860 (2023) - 2022
- [j43]Azza Abouzied, Peter J. Haas, Alexandra Meliou:
In-Database Decision Support: Opportunities and Challenges. IEEE Data Eng. Bull. 45(3): 102-115 (2022) - [c70]Sneha Gathani, Madelon Hulsebos, James Gale, Peter J. Haas, Çagatay Demiralp:
Augmenting Decision Making via Interactive What-If Analysis. CIDR 2022 - [c69]Wang Cen, Peter J. Haas:
Enhanced Simulation Metamodeling via Graph and Generative Neural Networks. WSC 2022: 2748-2759 - [i10]Sneha Gathani, Zhicheng Liu, Peter J. Haas, Çagatay Demiralp:
Predictive and Prescriptive Analytics in Business Decision Making: Needs and Concerns. CoRR abs/2212.13643 (2022) - 2021
- [i9]Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou:
Stochastic Package Queries in Probabilistic Databases. CoRR abs/2103.06784 (2021) - [i8]Sneha Gathani, Madelon Hulsebos, James Gale, Peter J. Haas, Çagatay Demiralp:
Augmenting Decision Making via Interactive What-If Analysis. CoRR abs/2109.06160 (2021) - 2020
- [j42]Anna Fariha, Matteo Brucato, Peter J. Haas, Alexandra Meliou:
SuDocu: Summarizing Documents by Example. Proc. VLDB Endow. 13(12): 2861-2864 (2020) - [j41]Matteo Brucato, Miro Mannino, Azza Abouzied, Peter J. Haas, Alexandra Meliou:
sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization. Proc. VLDB Endow. 13(12): 2881-2884 (2020) - [j40]Peter J. Haas, Georgios Theodoropoulos:
Introduction to the Special Issue for Towards an Ecosystem of Simulation Models and Data. ACM Trans. Model. Comput. Simul. 30(4): 20:1-20:3 (2020) - [c68]Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou:
Stochastic Package Queries in Probabilistic Databases. SIGMOD Conference 2020: 269-283 - [c67]Wang Cen, Emily A. Herbert, Peter J. Haas:
NIM: Modeling and Generation of Simulation Inputs Via Generative Neural Networks. WSC 2020: 584-595
2010 – 2019
- 2019
- [j39]Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald:
Compressed linear algebra for declarative large-scale machine learning. Commun. ACM 62(5): 83-91 (2019) - [j38]Brian Hentschel, Peter J. Haas, Yuanyuan Tian:
Online Model Management via Temporally Biased Sampling. SIGMOD Rec. 48(1): 69-76 (2019) - [j37]Brian Hentschel, Peter J. Haas, Yuanyuan Tian:
General Temporally Biased Sampling Schemes for Online Model Management. ACM Trans. Database Syst. 44(4): 14:1-14:45 (2019) - [c66]Emily A. Herbert, Wang Cen, Peter J. Haas:
NIM: generative neural networks for modeling and generation of simulation inputs. SummerSim 2019: 65:1-65:6 - [c65]Johanna Sommer, Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald, Peter J. Haas:
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions. SIGMOD Conference 2019: 1607-1623 - [i7]Brian Hentschel, Peter J. Haas, Yuanyuan Tian:
Temporally-Biased Sampling Schemes for Online Model Management. CoRR abs/1906.05677 (2019) - 2018
- [j36]Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald:
Compressed linear algebra for large-scale machine learning. VLDB J. 27(5): 719-744 (2018) - [c64]Brian Hentschel, Peter J. Haas, Yuanyuan Tian:
Temporally-Biased Sampling for Online Model Management. EDBT 2018: 109-120 - [r2]Peter J. Haas:
Karp-Luby Sampling. Encyclopedia of Database Systems (2nd ed.) 2018 - [r1]Peter J. Haas:
Monte Carlo Methods for Uncertain Data. Encyclopedia of Database Systems (2nd ed.) 2018 - [i6]Brian Hentschel, Peter J. Haas, Yuanyuan Tian:
Temporally-Biased Sampling for Online Model Management. CoRR abs/1801.09709 (2018) - [i5]Yeounoh Chung, Peter J. Haas, Eli Upfal, Tim Kraska:
Unknown Examples & Machine Learning Model Generalization. CoRR abs/1808.08294 (2018) - 2017
- [j35]Bum Chul Kwon, Janu Verma, Peter J. Haas, Çagatay Demiralp:
Sampling for Scalable Visual Analytics. IEEE Computer Graphics and Applications 37(1): 100-108 (2017) - [j34]Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati:
Foresight: Recommending Visual Insights. Proc. VLDB Endow. 10(12): 1937-1940 (2017) - [j33]Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald:
Scaling Machine Learning via Compressed Linear Algebra. SIGMOD Rec. 46(1): 42-49 (2017) - [i4]Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati:
Foresight: Recommending Visual Insights. CoRR abs/1707.03877 (2017) - [i3]Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati:
Foresight: Rapid Data Exploration Through Guideposts. CoRR abs/1709.10513 (2017) - 2016
- [j32]Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald:
Compressed Linear Algebra for Large-Scale Machine Learning. Proc. VLDB Endow. 9(12): 960-971 (2016) - [p1]Peter J. Haas:
Data-Stream Sampling: Basic Techniques and Results. Data Stream Management 2016: 13-44 - 2015
- [j31]Faraz Makari, Christina Teflioudi, Rainer Gemulla, Peter J. Haas, Yannis Sismanis:
Shared-memory and shared-nothing stochastic gradient descent algorithms for matrix completion. Knowl. Inf. Syst. 42(3): 493-523 (2015) - [j30]Peter W. Glynn, Peter J. Haas:
Guest Editors' Introduction to Special Issue Honoring Donald L. Iglehart. ACM Trans. Model. Comput. Simul. 25(4): 21:1-21:3 (2015) - [j29]Peter W. Glynn, Peter J. Haas:
On Transience and Recurrence in Irreducible Finite-State Stochastic Systems. ACM Trans. Model. Comput. Simul. 25(4): 25:1-25:19 (2015) - [c63]Liping Peng, Vuk Ercegovac, Kai Zeng, Peter J. Haas, Andrey Balmin, Yannis Sismanis:
Groupwise analytics via adaptive MapReduce. ICDE 2015: 1059-1070 - [c62]Wenlei Xie, Yuanyuan Tian, Yannis Sismanis, Andrey Balmin, Peter J. Haas:
Dynamic interaction graphs with probabilistic edge decay. ICDE 2015: 1143-1154 - [c61]Meenakshi Nagarajan, Angela D. Wilkins, Benjamin J. Bachman, Ilya B. Novikov, Shenghua Bao, Peter J. Haas, María E. Terrón-Díaz, Sumit Bhatia, Anbu K. Adikesavan, Jacques J. Labrie, Sam Regenbogen, Christie M. Buchovecky, Curtis R. Pickering, Linda Kato, Andreas Martin Lisewski, Ana Lelescu, Houyin Zhang, Stephen Boyer, Griff Weber, Ying Chen, Lawrence A. Donehower, W. Scott Spangler, Olivier Lichtarge:
Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature. KDD 2015: 2019-2028 - 2014
- [j28]Peter J. Haas, Shane G. Henderson, Pierre L'Ecuyer:
Guest editors' introduction to special issue on the third INFORMS simulation society research workshop. ACM Trans. Model. Comput. Simul. 24(1): 1:1-1:3 (2014) - [c60]W. Scott Spangler, Angela D. Wilkins, Benjamin J. Bachman, Meena Nagarajan, Tajhal Dayaram, Peter J. Haas, Sam Regenbogen, Curtis R. Pickering, Austin Comer, Jeffrey N. Myers, Ioana Stanoi, Linda Kato, Ana Lelescu, Jacques J. Labrie, Neha Parikh, Andreas Martin Lisewski, Lawrence A. Donehower, Ying Chen, Olivier Lichtarge:
Automated hypothesis generation based on mining scientific literature. KDD 2014: 1877-1886 - [c59]Peter J. Haas:
Model-data Ecosystems: challenges, tools, and trends. PODS 2014: 76-87 - [c58]Peter J. Haas:
Improving the efficiency of stochastic composite simulation models via result caching. WSC 2014: 817-828 - 2013
- [j27]Rainer Gemulla, Peter J. Haas, Wolfgang Lehner:
Non-uniformity issues and workarounds in bounded-size sampling. VLDB J. 22(6): 753-772 (2013) - [c57]Mohamed Y. Eltabakh, Fatma Özcan, Yannis Sismanis, Peter J. Haas, Hamid Pirahesh, Jan Vondrák:
Eagle-eyed elephant: split-oriented indexing in Hadoop. EDBT 2013: 89-100 - [c56]Zhuhua Cai, Zografoula Vagena, Luis Leopoldo Perez, Subramanian Arumugam, Peter J. Haas, Christopher M. Jermaine:
Simulation of database-valued markov chains using SimSQL. SIGMOD Conference 2013: 637-648 - [c55]Russell C. H. Cheng, Stewart Robinson, Peter J. Haas, Lee Schruben, Theresa M. Roeder:
Panel: Are we effectively preparing our students to be certified analytics professionals? WSC 2013: 3544-3555 - 2012
- [j26]Graham Cormode, Minos N. Garofalakis, Peter J. Haas, Chris Jermaine:
Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches. Found. Trends Databases 4(1-3): 1-294 (2012) - [c54]Peter J. Haas, Nicole C. Barberis, Piyaphol Phoungphol, Ignacio G. Terrizzano, Wang-Chiew Tan, Patricia G. Selinger, Paul P. Maglio:
Splash: Simulation optimization in complex systems of systems. Allerton Conference 2012: 414-425 - [c53]Niketan Pansare, Chris Jermaine, Peter J. Haas, Nitendra Rajput:
Topic Models over Spoken Language. ICDM 2012: 1062-1067 - [c52]Wang Chiew Tan, Peter J. Haas, Ronald L. Mak, Cheryl A. Kieliszewski, Patricia G. Selinger, Paul P. Maglio, Susanne Glissmann, Melissa Cefkin, Yinan Li:
Splash: a platform for analysis and simulation of health. IHI 2012: 543-552 - [c51]Peter W. Glynn, Peter J. Haas:
On simulation of non-Markovian stochastic Petri nets with heavy-tailed firing times. WSC 2012: 301:1-301:12 - 2011
- [j25]Peter J. Haas:
Sketches get sketchier. Commun. ACM 54(8): 100 (2011) - [j24]Joseph P. Bigus, Murray Campbell, Boaz Carmeli, Melissa Cefkin, Henry Chang, Ching-Hua Chen-Ritzo, William F. Cody, Shahram Ebadollahi, Alexandre V. Evfimievski, Ariel Farkash, Susanne Glissmann, David Gotz, Tyrone Grandison, Daniel Gruhl, Peter J. Haas, Mark J. H. Hsiao, Pei-Yun Sabrina Hsueh, Jianying Hu, Joseph M. Jasinski, James H. Kaufman, Cheryl A. Kieliszewski, Martin S. Kohn, Sarah E. Knoop, Paul P. Maglio, Ronald L. Mak, Haim Nelken, Chalapathy Neti, Hani Neuvirth, Yue Pan, Yardena Peres, Sreeram Ramakrishnan, Michal Rosen-Zvi, Sondra R. Renly, Pat Selinger, Amnon Shabo, Robert Sorrentino, Jimeng Sun, Tanveer Fathima Syeda-Mahmood, Wang Chiew Tan, Ying Y. Y. Tao, Reza Yaesoubi, Xinxin Zhu:
Information technology for healthcare transformation. IBM J. Res. Dev. 55(5): 6 (2011) - [j23]Peter J. Haas, Paul P. Maglio, Patricia G. Selinger, Wang Chiew Tan:
Data is Dead... Without What-If Models. Proc. VLDB Endow. 4(12): 1486-1489 (2011) - [j22]Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Perez, Chris Jermaine, Peter J. Haas:
The monte carlo database system: Stochastic analysis close to the data. ACM Trans. Database Syst. 36(3): 18:1-18:41 (2011) - [c50]Rainer Gemulla, Erik Nijkamp, Peter J. Haas, Yannis Sismanis:
Large-scale matrix factorization with distributed stochastic gradient descent. KDD 2011: 69-77 - 2010
- [j21]Subi Arumugam, Ravi Jampani, Luis Leopoldo Perez, Fei Xu, Christopher M. Jermaine, Peter J. Haas:
MCDB-R: Risk Analysis in the Database. Proc. VLDB Endow. 3(1): 782-793 (2010) - [c49]Peter J. Haas:
From MUD to MIRE: Managing Inherent Risk in the Enterprise. MUD 2010: 1-2 - [c48]Paul P. Maglio, Melissa Cefkin, Peter J. Haas, Patricia G. Selinger:
Social Factors in Creating an Integrated Capability for Health System Modeling and Simulation. SBP 2010: 44-51 - [c47]Sudipto Das, Yannis Sismanis, Kevin S. Beyer, Rainer Gemulla, Peter J. Haas, John McPherson:
Ricardo: integrating R and Hadoop. SIGMOD Conference 2010: 987-998
2000 – 2009
- 2009
- [j20]Kevin S. Beyer, Rainer Gemulla, Peter J. Haas, Berthold Reinwald, Yannis Sismanis:
Distinct-value synopses for multiset operations. Commun. ACM 52(10): 87-95 (2009) - [j19]Peter J. Haas, Ihab F. Ilyas, Guy M. Lohman, Volker Markl:
Discovering and Exploiting Statistical Properties for Query Optimization in Relational Databases: A Survey. Stat. Anal. Data Min. 1(4): 223-250 (2009) - [j18]Peter J. Haas, Dan Suciu:
Special issue on uncertain and probabilistic databases. VLDB J. 18(5): 987-988 (2009) - [c46]Yannis Sismanis, Ling Wang, Ariel Fuxman, Peter J. Haas, Berthold Reinwald:
Resolution-Aware Query Answering for Business Intelligence. ICDE 2009: 976-987 - [c45]Eirinaios Michelakis, Rajasekar Krishnamurthy, Peter J. Haas, Shivakumar Vaithyanathan:
Uncertainty management in rule-based information extraction systems. SIGMOD Conference 2009: 101-114 - [c44]Fei Xu, Kevin S. Beyer, Vuk Ercegovac, Peter J. Haas, Eugene J. Shekita:
E = MC3: managing uncertain enterprise data in a cluster-computing environment. SIGMOD Conference 2009: 441-454 - 2008
- [j17]Lin Qiao, Vijayshankar Raman, Frederick Reiss, Peter J. Haas, Guy M. Lohman:
Main-memory scan sharing for multi-core CPUs. Proc. VLDB Endow. 1(1): 610-621 (2008) - [j16]Rainer Gemulla, Wolfgang Lehner, Peter J. Haas:
Maintaining bounded-size sample synopses of evolving datasets. VLDB J. 17(2): 173-202 (2008) - [c43]Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Perez, Christopher M. Jermaine, Peter J. Haas:
MCDB: a monte carlo approach to managing uncertain data. SIGMOD Conference 2008: 687-700 - [i2]Christoph Koch, Peter J. Haas, Hans-Joachim Lenz, Dan Olteanu, Christopher Ré, Maurice van Keulen, Jeff Z. Pan:
08421 Working Group: Report of the Probabilistic Databases Benchmarking. Uncertainty Management in Information Systems 2008 - [i1]Anish Das Sarma, Ander de Keijzer, Amol Deshpande, Peter J. Haas, Ihab F. Ilyas, Christoph Koch, Thomas Neumann, Dan Olteanu, Martin Theobald, Vasilis Vassalos:
08421 Working Group: Classification, Representation and Modeling. Uncertainty Management in Information Systems 2008 - 2007
- [j15]Rainer Gemulla, Wolfgang Lehner, Peter J. Haas:
On reservoir sampling with deletions. Monde des Util. Anal. Données 36: 14-17 (2007) - [j14]Volker Markl, Peter J. Haas, Marcel Kutsch, Nimrod Megiddo, Utkarsh Srivastava, Tam Minh Tran:
Consistent selectivity estimation via maximum entropy. VLDB J. 16(1): 55-76 (2007) - [c42]Alexander Behm, Volker Markl, Peter J. Haas, Keshava Murthy:
Integrating Query-Feedback Based Statistics into Informix Dynamic Server. BTW 2007: 582-600 - [c41]Rainer Gemulla, Wolfgang Lehner, Peter J. Haas:
Maintaining bernoulli samples over evolving multisets. PODS 2007: 93-102 - [c40]Kevin S. Beyer, Peter J. Haas, Berthold Reinwald, Yannis Sismanis, Rainer Gemulla:
On synopses for distinct-value estimation under multiset operations. SIGMOD Conference 2007: 199-210 - [c39]Peter J. Haas, Fabian Hueske, Volker Markl:
Detecting Attribute Dependencies from Query Feedback. VLDB 2007: 830-841 - 2006
- [j13]Sam Lightstone, Guy M. Lohman, Peter J. Haas, Volker Markl, Jun Rao, Adam J. Storm, Maheswaran Surendra, Daniel C. Zilio:
Making DB2Products Self-Managing: Strategies and Experiences. IEEE Data Eng. Bull. 29(3): 16-23 (2006) - [c38]Marcel Kutsch, Peter J. Haas, Volker Markl, Nimrod Megiddo, Tam Minh Tran:
Integrating a Maximum-Entropy Cardinality Estimator into DB2 UDB. EDBT 2006: 1092-1096 - [c37]Paul G. Brown, Peter J. Haas:
Techniques for Warehousing of Sample Data. ICDE 2006: 6 - [c36]Utkarsh Srivastava, Peter J. Haas, Volker Markl, Marcel Kutsch, Tam Minh Tran:
ISOMER: Consistent Histogram Construction Using Query Feedback. ICDE 2006: 39 - [c35]Volker Markl, Marcel Kutsch, Tam Minh Tran, Peter J. Haas, Nimrod Megiddo:
MAXENT: consistent cardinality estimation in action. SIGMOD Conference 2006: 775-777 - [c34]Rainer Gemulla, Wolfgang Lehner, Peter J. Haas:
A Dip in the Reservoir: Maintaining Sample Synopses of Evolving Datasets. VLDB 2006: 595-606 - [c33]Yannis Sismanis, Paul Brown, Peter J. Haas, Berthold Reinwald:
GORDIAN: Efficient and Scalable Discovery of Composite Keys. VLDB 2006: 691-702 - 2005
- [c32]Paul Brown, Peter J. Haas, Jussi Myllymaki, Hamid Pirahesh, Berthold Reinwald, Yannis Sismanis:
Toward Automated Large-Scale Information Integration and Discovery. Data Management in a Connected World 2005: 161-180 - [c31]Peter J. Haas, Mokhtar Kandil, Alberto Lerner, Volker Markl, Ivan Popivanov, Vijayshankar Raman, Daniel C. Zilio:
Automated statistics collection in action. SIGMOD Conference 2005: 933-935 - [c30]Ning Zhang, Peter J. Haas, Vanja Josifovski, Guy M. Lohman, Chun Zhang:
Statistical Learning Techniques for Costing XML Queries. VLDB 2005: 289-300 - [c29]Volker Markl, Nimrod Megiddo, Marcel Kutsch, Tam Minh Tran, Peter J. Haas, Utkarsh Srivastava:
Consistently Estimating the Selectivity of Conjuncts of Predicates. VLDB 2005: 373-384 - 2004
- [c28]Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul G. Brown, Ashraf Aboulnaga:
Automatic Relationship Discovery in Self-Managing Database Systems. ICAC 2004: 340-341 - [c27]Peter J. Haas, Christian Koenig:
A Bi-Level Bernoulli Scheme for Database Sampling. SIGMOD Conference 2004: 275-286 - [c26]Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul Brown, Ashraf Aboulnaga:
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies. SIGMOD Conference 2004: 647-658 - [c25]Ashraf Aboulnaga, Peter J. Haas, Sam Lightstone, Guy M. Lohman, Volker Markl, Ivan Popivanov, Vijayshankar Raman:
Automated Statistics Collection in DB2 UDB. VLDB 2004: 1146-1157 - [c24]Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul G. Brown, Ashraf Aboulnaga:
CORDS: Automatic Generation of Correlation Statistics in DB2. VLDB 2004: 1341-1344 - [c23]Peter J. Haas:
Stochastic Petri Nets for Modelling and Simulation. WSC 2004: 101-112 - 2003
- [j12]Rakesh Agrawal, Peter J. Haas, Jerry Kiernan:
Watermarking relational data: framework, algorithms and analysis. VLDB J. 12(2): 157-169 (2003) - [c22]Hervé Brönnimann, Bin Chen, Manoranjan Dash, Peter J. Haas, Peter Scheuermann:
Efficient data reduction with EASE. KDD 2003: 59-68 - [c21]Rakesh Agrawal, Peter J. Haas, Jerry Kiernan:
A System for Watermarking Relational Databases. SIGMOD Conference 2003: 674 - [c20]Paul Brown, Peter J. Haas:
BHUNT: Automatic Discovery of Fuzzy Algebraic Constraints in Relational Data. VLDB 2003: 668-679 - 2002
- [b1]Peter J. Haas:
Stochastic Petri nets - modelling, stability, simulation. Springer series in operations research, Springer 2002, ISBN 978-0-387-95445-5, pp. I-XXII, 1-509 - [j11]Peter J. Haas, Peter W. Glynn:
On the validity of long-run estimation methods for discrete-event systems. SIGMETRICS Perform. Evaluation Rev. 30(3): 35-37 (2002) - [c19]Bin Chen, Peter J. Haas, Peter Scheuermann:
FAST: A New Sampling-Based Algorithm for Discovering Association Rules. ICDE 2002: 263 - [c18]Bin Chen, Peter J. Haas, Peter Scheuermann:
A new two-phase sampling based algorithm for discovering association rules. KDD 2002: 462-468 - [c17]Gang Luo, Curt J. Ellmann, Peter J. Haas, Jeffrey F. Naughton:
A scalable hash ripple join algorithm. SIGMOD Conference 2002: 252-262 - 2001
- [j10]Peter J. Haas:
Estimation of delays in non-regenerative discrete-event stochastic systems. SIGMETRICS Perform. Evaluation Rev. 28(4): 36-38 (2001) - [c16]Peter J. Haas, Joseph M. Hellerstein:
Online Query Processing. SIGMOD Conference 2001: 623
1990 – 1999
- 1999
- [j9]Joseph M. Hellerstein, Ron Avnur, Andy Chou, Christian Hidber, Chris Olston, Vijayshankar Raman, Tali Roth, Peter J. Haas:
Interactive data Analysis: The Control Project. Computer 32(8): 51-59 (1999) - [j8]Peter J. Haas:
Estimation Methods for Nonregenerative Stochastic Petri Nets. IEEE Trans. Software Eng. 25(2): 218-236 (1999) - [c15]Peter J. Haas, Joseph M. Hellerstein:
Ripple Joins for Online Aggregation. SIGMOD Conference 1999: 287-298 - [c14]Peter J. Haas:
Techniques for Online Exploration of Large Object-Relational Datasets. SSDBM 1999: 4-12 - 1997
- [j7]Daniel Barbará, William DuMouchel, Christos Faloutsos, Peter J. Haas, Joseph M. Hellerstein, Yannis E. Ioannidis, H. V. Jagadish, Theodore Johnson, Raymond T. Ng, Viswanath Poosala, Kenneth A. Ross, Kenneth C. Sevcik:
The New Jersey Data Reduction Report. IEEE Data Eng. Bull. 20(4): 3-45 (1997) - [c13]Peter J. Haas:
Estimation methods for stochastic Petri nets based on standardized time series. PNPM 1997: 194-204 - [c12]Joseph M. Hellerstein, Peter J. Haas, Helen J. Wang:
Online Aggregation. SIGMOD Conference 1997: 171-182 - [c11]Peter J. Haas:
Large-Sample and Deterministic Confidence Intervals for Online Aggregation. SSDBM 1997: 51-63 - 1996
- [j6]Peter J. Haas, Gerald S. Shedler:
Estimation methods for passage times using one-dependent cycles. Discret. Event Dyn. Syst. 6(1): 43-72 (1996) - [j5]Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, Arun N. Swami:
Selectivity and Cost Estimation for Joins Based on Random Sampling. J. Comput. Syst. Sci. 52(3): 550-569 (1996) - [c10]Viswanath Poosala, Yannis E. Ioannidis, Peter J. Haas, Eugene J. Shekita:
Improved Histograms for Selectivity Estimation of Range Predicates. SIGMOD Conference 1996: 294-305 - 1995
- [j4]Ulrich Lang, J. P. Peltier, Paul Christ, Stefan Rill, Dirk Rantzau, Harald Nebel, Andreas Wierse, Ruth E. Lang, Sylvain Causse, Frédéric Juaneda, Michel Grave, Peter J. Haas:
Perspectives of collaborative supercomputing and networking in European Aerospace research and industry. Future Gener. Comput. Syst. 11(4-5): 419-430 (1995) - [c9]Peter J. Haas, Arun N. Swami:
Sampling-Based Selectivity Estimation for Joins Using Augmented Frequent Value Statistics. ICDE 1995: 522-531 - [c8]Peter J. Haas, Gerald S. Shedler:
One-dependent cycles and passage times in stochastic Petri nets. PNPM 1995: 191-202 - [c7]Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, Lynne Stokes:
Sampling-Based Estimation of the Number of Distinct Values of an Attribute. VLDB 1995: 311-322 - 1994
- [c6]Peter J. Haas, Paul Christ:
Networking Issues in PAGEIN: The "N" of "HPCN". HPCN 1994: 86-93 - [c5]Peter J. Haas, Jeffrey F. Naughton, Arun N. Swami:
On the Relative Cost of Sampling for Join Selectivity Estimation. PODS 1994: 14-24 - 1993
- [c4]Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, Arun N. Swami:
Fixed-Precision Estimation of Join Selectivity. PODS 1993: 190-201 - 1992
- [c3]Peter J. Haas, Arun N. Swami:
Sequential Sampling Procedures for Query Size Estimation. SIGMOD Conference 1992: 341-350
1980 – 1989
- 1989
- [j3]Peter J. Haas, Gerald S. Shedler:
Stochastic Petri Net Representation of Discrete Event Simulations. IEEE Trans. Software Eng. 15(4): 381-393 (1989) - 1987
- [c2]Peter J. Haas, Gerald S. Shedler:
Stochastic Petri Nets with Simultaneous Transition Firings. PNPM 1987: 24-33 - 1986
- [j2]Peter J. Haas, Gerald S. Shedler:
Regenerative Stochastic Petri Nets. Perform. Evaluation 6(3): 189-204 (1986) - 1985
- [j1]Peter J. Haas, Gerald S. Shedler:
Regenerative Simulation Methods for Local Area Computer Networks. IBM J. Res. Dev. 29(2): 194-205 (1985) - [c1]Peter J. Haas, Gerald S. Shedler:
Regenerative Simulation of Stochastic Petri Nets. PNPM 1985: 14-21
Coauthor Index
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