Peter J. Haas - RankMe

141 papers A* 27A 2B 5Misc 10Journal 58Unranked 35

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Data Management Perspectives on Prescriptive Analytics (Invited Talk). ICDT Alexandra Meliou, Azza Abouzied, Peter J. Haas, Riddho R. Haque, Anh L. Mai, Vasileios Vittis
2025	—	`conf`	Embedding Ethical Awareness in Computer Science and AI Education: The PEaRCE Approach to Responsible Computing. AIED (1) Mohammad Hadi Nezhad, Francisco Enrique Vicente Castro, Eugene Mak, Peter J. Haas, Danielle Allessio, Leon J. Osterweil, Injila Rasul, Heather M. Conboy, Ivon Arroyo
2025	J	`jnl`	PRAXA: A Framework for What-If Analysis. CoRR Sneha Gathani, Kevin Li, Raghav Thind, Sirui Zeng, Matthew Xu, Peter J. Haas, Çagatay Demiralp, Zhicheng Liu
2025	J	`jnl`	Stochastic SketchRefine: Scaling In-Database Decision-Making under Uncertainty to Millions of Tuples. Proc. VLDB Endow. Riddho R. Haque, Anh L. Mai, Matteo Brucato, Azza Abouzied, Peter J. Haas, Alexandra Meliou
2025	A*	`conf`	What-if Analysis for Business Professionals: Current Practices and Future Opportunities. CHI Sneha Gathani, Zhicheng Liu, Peter J. Haas, Çagatay Demiralp
2024	J	`jnl`	Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization. Proc. VLDB Endow. Anh L. Mai, Pengyu Wang, Azza Abouzied, Matteo Brucato, Peter J. Haas, Alexandra Meliou
2024	J	`jnl`	Stochastic SketchRefine: Scaling In-Database Decision-Making under Uncertainty to Millions of Tuples. CoRR Riddho R. Haque, Anh L. Mai, Matteo Brucato, Azza Abouzied, Peter J. Haas, Alexandra Meliou
2024	Misc	`conf`	Tutorial: Artificial Neural Networks for Discrete-Event Simulation. WSC Peter J. Haas
2023	Misc	`conf`	Causal Dynamic Bayesian Networks for Simulation Metamodeling. WSC Pracheta Amaranath, Peter J. Haas, David D. Jensen, Sam Witty
2023	Misc	`conf`	Efficient Hybrid Simulation Optimization via Graph Neural Network Metamodeling. WSC Wang Cen, Peter J. Haas
2023	J	`jnl`	Exact PPS sampling with bounded sample size. Inf. Process. Lett. Brian Hentschel, Peter J. Haas, Yuanyuan Tian
2023	J	`jnl`	NIM: Generative Neural Networks for Automated Modeling and Generation of Simulation Inputs. ACM Trans. Model. Comput. Simul. Wang Cen, Peter J. Haas
2023	—	`conf`	Piloting an Interactive Ethics and Responsible Computing Learning Environment in Undergraduate CS Courses. SIGCSE (1) Francisco Castro, Sahitya Raipura, Heather M. Conboy, Peter J. Haas, Leon J. Osterweil, Ivon Arroyo
2023	J	`jnl`	Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization. CoRR Anh L. Mai, Pengyu Wang, Azza Abouzied, Matteo Brucato, Peter J. Haas, Alexandra Meliou
2022	A	`conf`	Augmenting Decision Making via Interactive What-If Analysis. CIDR Sneha Gathani, Madelon Hulsebos, James Gale, Peter J. Haas, Çagatay Demiralp
2022	Misc	`conf`	Enhanced Simulation Metamodeling via Graph and Generative Neural Networks. WSC Wang Cen, Peter J. Haas
2022	J	`jnl`	In-Database Decision Support: Opportunities and Challenges. IEEE Data Eng. Bull. Azza Abouzied, Peter J. Haas, Alexandra Meliou
2022	J	`jnl`	Predictive and Prescriptive Analytics in Business Decision Making: Needs and Concerns. CoRR Sneha Gathani, Zhicheng Liu, Peter J. Haas, Çagatay Demiralp
2021	J	`jnl`	Augmenting Decision Making via Interactive What-If Analysis. CoRR Sneha Gathani, Madelon Hulsebos, James Gale, Peter J. Haas, Çagatay Demiralp
2021	J	`jnl`	Stochastic Package Queries in Probabilistic Databases. CoRR Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou
2020	J	`jnl`	Introduction to the Special Issue for Towards an Ecosystem of Simulation Models and Data. ACM Trans. Model. Comput. Simul. Peter J. Haas, Georgios Theodoropoulos
2020	Misc	`conf`	NIM: Modeling and Generation of Simulation Inputs Via Generative Neural Networks. WSC Wang Cen, Emily A. Herbert, Peter J. Haas
2020	—	`conf`	Stochastic Package Queries in Probabilistic Databases. SIGMOD Conference Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou
2020	J	`jnl`	SuDocu: Summarizing Documents by Example. Proc. VLDB Endow. Anna Fariha, Matteo Brucato, Peter J. Haas, Alexandra Meliou
2020	J	`jnl`	sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization. Proc. VLDB Endow. Matteo Brucato, Miro Mannino, Azza Abouzied, Peter J. Haas, Alexandra Meliou
2019	J	`jnl`	Compressed linear algebra for declarative large-scale machine learning. Commun. ACM Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald
2019	J	`jnl`	General Temporally Biased Sampling Schemes for Online Model Management. ACM Trans. Database Syst. Brian Hentschel, Peter J. Haas, Yuanyuan Tian
2019	—	`conf`	MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions. SIGMOD Conference Johanna Sommer, Matthias Boehm, Alexandre V. Evfimievski, Berthold Reinwald, Peter J. Haas
2019	—	`conf`	NIM: generative neural networks for modeling and generation of simulation inputs. SummerSim Emily A. Herbert, Wang Cen, Peter J. Haas
2019	J	`jnl`	Online Model Management via Temporally Biased Sampling. SIGMOD Rec. Brian Hentschel, Peter J. Haas, Yuanyuan Tian
2019	J	`jnl`	Temporally-Biased Sampling Schemes for Online Model Management. CoRR Brian Hentschel, Peter J. Haas, Yuanyuan Tian
2018	J	`jnl`	Compressed linear algebra for large-scale machine learning. VLDB J. Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald
2018	—	`ch.`	Karp-Luby Sampling. Encyclopedia of Database Systems (2nd ed.) Peter J. Haas
2018	—	`ch.`	Monte Carlo Methods for Uncertain Data. Encyclopedia of Database Systems (2nd ed.) Peter J. Haas
2018	B	`conf`	Temporally-Biased Sampling for Online Model Management. EDBT Brian Hentschel, Peter J. Haas, Yuanyuan Tian
2018	J	`jnl`	Temporally-Biased Sampling for Online Model Management. CoRR Brian Hentschel, Peter J. Haas, Yuanyuan Tian
2018	J	`jnl`	Unknown Examples & Machine Learning Model Generalization. CoRR Yeounoh Chung, Peter J. Haas, Eli Upfal, Tim Kraska
2017	J	`jnl`	Foresight: Rapid Data Exploration Through Guideposts. CoRR Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati
2017	J	`jnl`	Foresight: Recommending Visual Insights. CoRR Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati
2017	J	`jnl`	Foresight: Recommending Visual Insights. Proc. VLDB Endow. Çagatay Demiralp, Peter J. Haas, Srinivasan Parthasarathy, Tejaswini Pedapati
2017	J	`jnl`	Sampling for Scalable Visual Analytics. IEEE Computer Graphics and Applications Bum Chul Kwon, Janu Verma, Peter J. Haas, Çagatay Demiralp
2017	J	`jnl`	Scaling Machine Learning via Compressed Linear Algebra. SIGMOD Rec. Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald
2016	J	`jnl`	Compressed Linear Algebra for Large-Scale Machine Learning. Proc. VLDB Endow. Ahmed Elgohary, Matthias Boehm, Peter J. Haas, Frederick R. Reiss, Berthold Reinwald
2016	—	`ch.`	Data-Stream Sampling: Basic Techniques and Results. Data Stream Management Peter J. Haas
2015	A*	`conf`	Dynamic interaction graphs with probabilistic edge decay. ICDE Wenlei Xie, Yuanyuan Tian, Yannis Sismanis, Andrey Balmin, Peter J. Haas
2015	A*	`conf`	Groupwise analytics via adaptive MapReduce. ICDE Liping Peng, Vuk Ercegovac, Kai Zeng, Peter J. Haas, Andrey Balmin, Yannis Sismanis
2015	J	`jnl`	Guest Editors' Introduction to Special Issue Honoring Donald L. Iglehart. ACM Trans. Model. Comput. Simul. Peter W. Glynn, Peter J. Haas
2015	J	`jnl`	On Transience and Recurrence in Irreducible Finite-State Stochastic Systems. ACM Trans. Model. Comput. Simul. Peter W. Glynn, Peter J. Haas
2015	A*	`conf`	Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature. KDD 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
2015	J	`jnl`	Shared-memory and shared-nothing stochastic gradient descent algorithms for matrix completion. Knowl. Inf. Syst. Faraz Makari, Christina Teflioudi, Rainer Gemulla, Peter J. Haas, Yannis Sismanis
2014	A*	`conf`	Automated hypothesis generation based on mining scientific literature. KDD 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
2014	J	`jnl`	Guest editors' introduction to special issue on the third INFORMS simulation society research workshop. ACM Trans. Model. Comput. Simul. Peter J. Haas, Shane G. Henderson, Pierre L'Ecuyer
2014	Misc	`conf`	Improving the efficiency of stochastic composite simulation models via result caching. WSC Peter J. Haas
2014	A*	`conf`	Model-data Ecosystems: challenges, tools, and trends. PODS Peter J. Haas
2013	B	`conf`	Eagle-eyed elephant: split-oriented indexing in Hadoop. EDBT Mohamed Y. Eltabakh, Fatma Özcan, Yannis Sismanis, Peter J. Haas, Hamid Pirahesh, Jan Vondrák
2013	J	`jnl`	Non-uniformity issues and workarounds in bounded-size sampling. VLDB J. Rainer Gemulla, Peter J. Haas, Wolfgang Lehner
2013	Misc	`conf`	Panel: Are we effectively preparing our students to be certified analytics professionals? WSC Russell C. H. Cheng, Stewart Robinson, Peter J. Haas, Lee Schruben, Theresa M. Roeder
2013	—	`conf`	Simulation of database-valued markov chains using SimSQL. SIGMOD Conference Zhuhua Cai, Zografoula Vagena, Luis Leopoldo Perez, Subramanian Arumugam, Peter J. Haas, Christopher M. Jermaine
2012	Misc	`conf`	On simulation of non-Markovian stochastic Petri nets with heavy-tailed firing times. WSC Peter W. Glynn, Peter J. Haas
2012	—	`conf`	Splash: Simulation optimization in complex systems of systems. Allerton Conference Peter J. Haas, Nicole C. Barberis, Piyaphol Phoungphol, Ignacio G. Terrizzano, Wang-Chiew Tan, Patricia G. Selinger, Paul P. Maglio
2012	—	`conf`	Splash: a platform for analysis and simulation of health. IHI Wang Chiew Tan, Peter J. Haas, Ronald L. Mak, Cheryl A. Kieliszewski, Patricia G. Selinger, Paul P. Maglio, Susanne Glissmann, Melissa Cefkin, Yinan Li
2012	J	`jnl`	Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches. Found. Trends Databases Graham Cormode, Minos N. Garofalakis, Peter J. Haas, Chris Jermaine
2012	A*	`conf`	Topic Models over Spoken Language. ICDM Niketan Pansare, Chris Jermaine, Peter J. Haas, Nitendra Rajput
2011	J	`jnl`	Data is Dead... Without What-If Models. Proc. VLDB Endow. Peter J. Haas, Paul P. Maglio, Patricia G. Selinger, Wang Chiew Tan
2011	J	`jnl`	Information technology for healthcare transformation. IBM J. Res. Dev. 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
2011	A*	`conf`	Large-scale matrix factorization with distributed stochastic gradient descent. KDD Rainer Gemulla, Erik Nijkamp, Peter J. Haas, Yannis Sismanis
2011	J	`jnl`	Sketches get sketchier. Commun. ACM Peter J. Haas
2011	J	`jnl`	The monte carlo database system: Stochastic analysis close to the data. ACM Trans. Database Syst. Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Perez, Chris Jermaine, Peter J. Haas
2010	—	`conf`	From MUD to MIRE: Managing Inherent Risk in the Enterprise. MUD Peter J. Haas
2010	J	`jnl`	MCDB-R: Risk Analysis in the Database. Proc. VLDB Endow. Subi Arumugam, Ravi Jampani, Luis Leopoldo Perez, Fei Xu, Christopher M. Jermaine, Peter J. Haas
2010	—	`conf`	Ricardo: integrating R and Hadoop. SIGMOD Conference Sudipto Das, Yannis Sismanis, Kevin S. Beyer, Rainer Gemulla, Peter J. Haas, John McPherson
2010	—	`conf`	Social Factors in Creating an Integrated Capability for Health System Modeling and Simulation. SBP Paul P. Maglio, Melissa Cefkin, Peter J. Haas, Patricia G. Selinger
2009	J	`jnl`	Discovering and Exploiting Statistical Properties for Query Optimization in Relational Databases: A Survey. Stat. Anal. Data Min. Peter J. Haas, Ihab F. Ilyas, Guy M. Lohman, Volker Markl
2009	J	`jnl`	Distinct-value synopses for multiset operations. Commun. ACM Kevin S. Beyer, Rainer Gemulla, Peter J. Haas, Berthold Reinwald, Yannis Sismanis
2009	—	`conf`	E = MC SIGMOD Conference Fei Xu, Kevin S. Beyer, Vuk Ercegovac, Peter J. Haas, Eugene J. Shekita
2009	A*	`conf`	Resolution-Aware Query Answering for Business Intelligence. ICDE Yannis Sismanis, Ling Wang, Ariel Fuxman, Peter J. Haas, Berthold Reinwald
2009	J	`jnl`	Special issue on uncertain and probabilistic databases. VLDB J. Peter J. Haas, Dan Suciu
2009	—	`conf`	Uncertainty management in rule-based information extraction systems. SIGMOD Conference Eirinaios Michelakis, Rajasekar Krishnamurthy, Peter J. Haas, Shivakumar Vaithyanathan
2008	—	`conf`	08421 Working Group: Classification, Representation and Modeling. Uncertainty Management in Information Systems Anish Das Sarma, Ander de Keijzer, Amol Deshpande, Peter J. Haas, Ihab F. Ilyas, Christoph Koch, Thomas Neumann, Dan Olteanu, Martin Theobald, Vasilis Vassalos
2008	—	`conf`	08421 Working Group: Report of the Probabilistic Databases Benchmarking. Uncertainty Management in Information Systems Christoph Koch, Peter J. Haas, Hans-Joachim Lenz, Dan Olteanu, Christopher Ré, Maurice van Keulen, Jeff Z. Pan
2008	—	`conf`	MCDB: a monte carlo approach to managing uncertain data. SIGMOD Conference Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Perez, Christopher M. Jermaine, Peter J. Haas
2008	J	`jnl`	Main-memory scan sharing for multi-core CPUs. Proc. VLDB Endow. Lin Qiao, Vijayshankar Raman, Frederick Reiss, Peter J. Haas, Guy M. Lohman
2008	J	`jnl`	Maintaining bounded-size sample synopses of evolving datasets. VLDB J. Rainer Gemulla, Wolfgang Lehner, Peter J. Haas
2007	J	`jnl`	Consistent selectivity estimation via maximum entropy. VLDB J. Volker Markl, Peter J. Haas, Marcel Kutsch, Nimrod Megiddo, Utkarsh Srivastava, Tam Minh Tran
2007	A*	`conf`	Detecting Attribute Dependencies from Query Feedback. VLDB Peter J. Haas, Fabian Hueske, Volker Markl
2007	Misc	`conf`	Integrating Query-Feedback Based Statistics into Informix Dynamic Server. BTW Alexander Behm, Volker Markl, Peter J. Haas, Keshava Murthy
2007	A*	`conf`	Maintaining bernoulli samples over evolving multisets. PODS Rainer Gemulla, Wolfgang Lehner, Peter J. Haas
2007	J	`jnl`	On reservoir sampling with deletions. Monde des Util. Anal. Données Rainer Gemulla, Wolfgang Lehner, Peter J. Haas
2007	—	`conf`	On synopses for distinct-value estimation under multiset operations. SIGMOD Conference Kevin S. Beyer, Peter J. Haas, Berthold Reinwald, Yannis Sismanis, Rainer Gemulla
2006	A*	`conf`	A Dip in the Reservoir: Maintaining Sample Synopses of Evolving Datasets. VLDB Rainer Gemulla, Wolfgang Lehner, Peter J. Haas
2006	A*	`conf`	GORDIAN: Efficient and Scalable Discovery of Composite Keys. VLDB Yannis Sismanis, Paul Brown, Peter J. Haas, Berthold Reinwald
2006	A*	`conf`	ISOMER: Consistent Histogram Construction Using Query Feedback. ICDE Utkarsh Srivastava, Peter J. Haas, Volker Markl, Marcel Kutsch, Tam Minh Tran
2006	B	`conf`	Integrating a Maximum-Entropy Cardinality Estimator into DB2 UDB. EDBT Marcel Kutsch, Peter J. Haas, Volker Markl, Nimrod Megiddo, Tam Minh Tran
2006	—	`conf`	MAXENT: consistent cardinality estimation in action. SIGMOD Conference Volker Markl, Marcel Kutsch, Tam Minh Tran, Peter J. Haas, Nimrod Megiddo
2006	J	`jnl`	Making DB2Products Self-Managing: Strategies and Experiences. IEEE Data Eng. Bull. Sam Lightstone, Guy M. Lohman, Peter J. Haas, Volker Markl, Jun Rao, Adam J. Storm, Maheswaran Surendra, Daniel C. Zilio
2006	A*	`conf`	Techniques for Warehousing of Sample Data. ICDE Paul G. Brown, Peter J. Haas
2005	—	`conf`	Automated statistics collection in action. SIGMOD Conference Peter J. Haas, Mokhtar Kandil, Alberto Lerner, Volker Markl, Ivan Popivanov, Vijayshankar Raman, Daniel C. Zilio
2005	A*	`conf`	Consistently Estimating the Selectivity of Conjuncts of Predicates. VLDB Volker Markl, Nimrod Megiddo, Marcel Kutsch, Tam Minh Tran, Peter J. Haas, Utkarsh Srivastava
2005	A*	`conf`	Statistical Learning Techniques for Costing XML Queries. VLDB Ning Zhang, Peter J. Haas, Vanja Josifovski, Guy M. Lohman, Chun Zhang
2005	—	`conf`	Toward Automated Large-Scale Information Integration and Discovery. Data Management in a Connected World Paul Brown, Peter J. Haas, Jussi Myllymaki, Hamid Pirahesh, Berthold Reinwald, Yannis Sismanis
2004	—	`conf`	A Bi-Level Bernoulli Scheme for Database Sampling. SIGMOD Conference Peter J. Haas, Christian Koenig
2004	A*	`conf`	Automated Statistics Collection in DB2 UDB. VLDB Ashraf Aboulnaga, Peter J. Haas, Sam Lightstone, Guy M. Lohman, Volker Markl, Ivan Popivanov, Vijayshankar Raman
2004	—	`conf`	Automatic Relationship Discovery in Self-Managing Database Systems. ICAC Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul G. Brown, Ashraf Aboulnaga
2004	—	`conf`	CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies. SIGMOD Conference Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul Brown, Ashraf Aboulnaga
2004	A*	`conf`	CORDS: Automatic Generation of Correlation Statistics in DB2. VLDB Ihab F. Ilyas, Volker Markl, Peter J. Haas, Paul G. Brown, Ashraf Aboulnaga
2004	Misc	`conf`	Stochastic Petri Nets for Modelling and Simulation. WSC Peter J. Haas
2003	—	`conf`	A System for Watermarking Relational Databases. SIGMOD Conference Rakesh Agrawal, Peter J. Haas, Jerry Kiernan
2003	A*	`conf`	BHUNT: Automatic Discovery of Fuzzy Algebraic Constraints in Relational Data. VLDB Paul Brown, Peter J. Haas
2003	A*	`conf`	Efficient data reduction with EASE. KDD Hervé Brönnimann, Bin Chen, Manoranjan Dash, Peter J. Haas, Peter Scheuermann
2003	J	`jnl`	Watermarking relational data: framework, algorithms and analysis. VLDB J. Rakesh Agrawal, Peter J. Haas, Jerry Kiernan
2002	A*	`conf`	A new two-phase sampling based algorithm for discovering association rules. KDD Bin Chen, Peter J. Haas, Peter Scheuermann
2002	—	`conf`	A scalable hash ripple join algorithm. SIGMOD Conference Gang Luo, Curt J. Ellmann, Peter J. Haas, Jeffrey F. Naughton
2002	A*	`conf`	FAST: A New Sampling-Based Algorithm for Discovering Association Rules. ICDE Bin Chen, Peter J. Haas, Peter Scheuermann
2002	J	`jnl`	On the validity of long-run estimation methods for discrete-event systems. SIGMETRICS Perform. Evaluation Rev. Peter J. Haas, Peter W. Glynn
2002	—	`book`	Stochastic Petri nets - modelling, stability, simulation. Peter J. Haas
2001	J	`jnl`	Estimation of delays in non-regenerative discrete-event stochastic systems. SIGMETRICS Perform. Evaluation Rev. Peter J. Haas
2001	—	`conf`	Online Query Processing. SIGMOD Conference Peter J. Haas, Joseph M. Hellerstein
1999	J	`jnl`	Estimation Methods for Nonregenerative Stochastic Petri Nets. IEEE Trans. Software Eng. Peter J. Haas
1999	J	`jnl`	Interactive data Analysis: The Control Project. Computer Joseph M. Hellerstein, Ron Avnur, Andy Chou, Christian Hidber, Chris Olston, Vijayshankar Raman, Tali Roth, Peter J. Haas
1999	—	`conf`	Ripple Joins for Online Aggregation. SIGMOD Conference Peter J. Haas, Joseph M. Hellerstein
1999	B	`conf`	Techniques for Online Exploration of Large Object-Relational Datasets. SSDBM Peter J. Haas
1997	—	`conf`	Estimation methods for stochastic Petri nets based on standardized time series. PNPM Peter J. Haas
1997	B	`conf`	Large-Sample and Deterministic Confidence Intervals for Online Aggregation. SSDBM Peter J. Haas
1997	—	`conf`	Online Aggregation. SIGMOD Conference Joseph M. Hellerstein, Peter J. Haas, Helen J. Wang
1997	J	`jnl`	The New Jersey Data Reduction Report. IEEE Data Eng. Bull. 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
1996	J	`jnl`	Estimation methods for passage times using one-dependent cycles. Discret. Event Dyn. Syst. Peter J. Haas, Gerald S. Shedler
1996	—	`conf`	Improved Histograms for Selectivity Estimation of Range Predicates. SIGMOD Conference Viswanath Poosala, Yannis E. Ioannidis, Peter J. Haas, Eugene J. Shekita
1996	J	`jnl`	Selectivity and Cost Estimation for Joins Based on Random Sampling. J. Comput. Syst. Sci. Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, Arun N. Swami
1995	—	`conf`	One-dependent cycles and passage times in stochastic Petri nets. PNPM Peter J. Haas, Gerald S. Shedler
1995	J	`jnl`	Perspectives of collaborative supercomputing and networking in European Aerospace research and industry. Future Gener. Comput. Syst. 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
1995	A*	`conf`	Sampling-Based Estimation of the Number of Distinct Values of an Attribute. VLDB Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, Lynne Stokes
1995	A*	`conf`	Sampling-Based Selectivity Estimation for Joins Using Augmented Frequent Value Statistics. ICDE Peter J. Haas, Arun N. Swami
1994	—	`conf`	Networking Issues in PAGEIN: The "N" of "HPCN". HPCN Peter J. Haas, Paul Christ
1994	A*	`conf`	On the Relative Cost of Sampling for Join Selectivity Estimation. PODS Peter J. Haas, Jeffrey F. Naughton, Arun N. Swami
1993	A*	`conf`	Fixed-Precision Estimation of Join Selectivity. PODS Peter J. Haas, Jeffrey F. Naughton, S. Seshadri, Arun N. Swami
1992	—	`conf`	Sequential Sampling Procedures for Query Size Estimation. SIGMOD Conference Peter J. Haas, Arun N. Swami
1989	J	`jnl`	Stochastic Petri Net Representation of Discrete Event Simulations. IEEE Trans. Software Eng. Peter J. Haas, Gerald S. Shedler
1987	—	`conf`	Stochastic Petri Nets with Simultaneous Transition Firings. PNPM Peter J. Haas, Gerald S. Shedler
1986	J	`jnl`	Regenerative Stochastic Petri Nets. Perform. Evaluation Peter J. Haas, Gerald S. Shedler
1985	J	`jnl`	Regenerative Simulation Methods for Local Area Computer Networks. IBM J. Res. Dev. Peter J. Haas, Gerald S. Shedler
1985	—	`conf`	Regenerative Simulation of Stochastic Petri Nets. PNPM Peter J. Haas, Gerald S. Shedler