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ORCIDEli Upfal
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- affiliation: Brown University, Providence, USA
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2020 – today
- 2024
[i46]Megumi Ando, Anna Lysyanskaya, Eli Upfal:
Bruisable Onions: Anonymous Communication in the Asynchronous Model. IACR Cryptol. ePrint Arch. 2024: 885 (2024)- 2023
- [c136]Alessio Mazzetto, Eli Upfal:
Nonparametric Density Estimation under Distribution Drift. ICML 2023: 24251-24270 - [c135]Alessio Mazzetto, Eli Upfal:
An Adaptive Algorithm for Learning with Unknown Distribution Drift. NeurIPS 2023 - [i45]Alessio Mazzetto, Eli Upfal:
Nonparametric Density Estimation under Distribution Drift. CoRR abs/2302.02460 (2023) - [i44]Alessio Mazzetto, Eli Upfal:
An Adaptive Algorithm for Learning with Unknown Distribution Drift. CoRR abs/2305.02252 (2023) - [i43]Alessio Mazzetto, Reza Esfandiarpoor, Eli Upfal, Stephen H. Bach:
An Adaptive Method for Weak Supervision with Drifting Data. CoRR abs/2306.01658 (2023) - 2022
- [j78]Shahrzad Haddadan
, Cristina Menghini, Matteo Riondato, Eli Upfal:
Reducing polarization and increasing diverse navigability in graphs by inserting edges and swapping edge weights. Data Min. Knowl. Discov. 36(6): 2334-2378 (2022) - [j77]John Augustine, William K. Moses Jr., Amanda Redlich, Eli Upfal:
Balanced Allocation: Patience Is Not a Virtue. SIAM J. Comput. 51(6): 1743-1768 (2022) - [c134]Alessio Mazzetto, Cristina Menghini, Andrew Yuan, Eli Upfal, Stephen H. Bach:
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes. NeurIPS 2022 - [i42]Alessio Mazzetto, Cristina Menghini, Andrew Yuan, Eli Upfal, Stephen H. Bach:
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes. CoRR abs/2205.13068 (2022) - 2021
- [j76]Lorenzo De Stefani, Erisa Terolli, Eli Upfal:
Tiered Sampling: An Efficient Method for Counting Sparse Motifs in Massive Graph Streams. ACM Trans. Knowl. Discov. Data 15(5): 79:1-79:52 (2021) - [c133]Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, Stephen H. Bach:
Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees. AISTATS 2021: 3196-3204 - [c132]Cristina Menghini, Aris Anagnostopoulos, Eli Upfal:
How Inclusive Are Wikipedia's Hyperlinks in Articles Covering Polarizing Topics? IEEE BigData 2021: 1300-1307 - [c131]Megumi Ando, Anna Lysyanskaya, Eli Upfal:
On the Complexity of Anonymous Communication Through Public Networks. ITC 2021: 9:1-9:25 - [c130]Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H. Bach, Eli Upfal:
Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees. ICML 2021: 7534-7543 - [c129]Shahrzad Haddadan, Yue Zhuang, Cyrus Cousins, Eli Upfal:
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds. NeurIPS 2021: 25760-25772 - [c128]Shahrzad Haddadan, Cristina Menghini, Matteo Riondato, Eli Upfal:
RePBubLik: Reducing Polarized Bubble Radius with Link Insertions. WSDM 2021: 139-147 - [i41]Shahrzad Haddadan, Cristina Menghini, Matteo Riondato, Eli Upfal:
RePBubLik: Reducing the Polarized Bubble Radius with Link Insertions. CoRR abs/2101.04751 (2021) - [i40]Shahrzad Haddadan, Yue Zhuang, Cyrus Cousins, Eli Upfal:
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds. CoRR abs/2111.07372 (2021) - [i39]Nathan Tung, Eli Upfal, Jerome N. Sanes, Ani Eloyan:
Neuro-Hotnet: A Graph Theoretic Approach for Brain FC Estimation. CoRR abs/2111.08118 (2021) - 2020
- [j75]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
Distributed Graph Diameter Approximation. Algorithms 13(9): 216 (2020) - [i38]Cristina Menghini, Aris Anagnostopoulos, Eli Upfal:
Wikipedia's Network Bias on Controversial Topics. CoRR abs/2007.08197 (2020) - [i37]Cyrus Cousins, Shahrzad Haddadan, Eli Upfal:
Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE. CoRR abs/2011.11129 (2020)
2010 – 2019
- 2019
- [j74]Morteza Chalabi Hajkarim, Eli Upfal, Fabio Vandin:
Differentially mutated subnetworks discovery. Algorithms Mol. Biol. 14(1): 10:1-10:11 (2019) - [j73]Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal:
Bandits and Experts in Metric Spaces. J. ACM 66(4): 30:1-30:77 (2019) - [j72]Ahmad Mahmoody, Eli Upfal:
Optimizing static and adaptive probing schedules for rapid event detection. Theor. Comput. Sci. 774: 14-30 (2019) - [c127]Enrique Areyan Viqueira, Amy Greenwald, Cyrus Cousins, Eli Upfal:
Learning Simulation-Based Games from Data. AAMAS 2019: 1778-1780 - [c126]Benedetto Buratti, Eli Upfal:
Ordalia: Deep Learning Hyperparameter Search via Generalization Error Bounds Extrapolation. IEEE BigData 2019: 180-187 - [c125]Cristina Menghini, Aris Anagnostopoulos, Eli Upfal:
Wikipedia Polarization and Its Effects on Navigation Paths. IEEE BigData 2019: 6154-6156 - [c124]Lorenzo De Stefani, Eli Upfal:
A Rademacher Complexity Based Method for Controlling Power and Confidence Level in Adaptive Statistical Analysis. DSAA 2019: 71-80 - [c123]Lorenzo De Stefani, Leonhard F. Spiegelberg, Eli Upfal, Tim Kraska:
VizCertify: A Framework for Secure Visual Data Exploration. DSAA 2019: 241-251 - [c122]Zeyuan Shang, Emanuel Zgraggen, Benedetto Buratti, Ferdinand Kossmann, Philipp Eichmann, Yeounoh Chung, Carsten Binnig, Eli Upfal, Tim Kraska:
Democratizing Data Science through Interactive Curation of ML Pipelines. SIGMOD Conference 2019: 1171-1188 - [i36]Megumi Ando, Anna Lysyanskaya, Eli Upfal:
On the Complexity of Anonymous Communication Through Public Networks. CoRR abs/1902.06306 (2019) - [i35]Enrique Areyan Viqueira, Cyrus Cousins, Eli Upfal, Amy Greenwald:
Learning Equilibria of Simulation-Based Games. CoRR abs/1905.13379 (2019) - [i34]Lorenzo De Stefani, Eli Upfal:
A Rademacher Complexity Based Method fo rControlling Power and Confidence Level in Adaptive Statistical Analysis. CoRR abs/1910.03493 (2019) - 2018
- [j71]Alessandro Epasto, Eli Upfal:
Efficient Approximation for Restricted Biclique Cover Problems. Algorithms 11(6): 84 (2018) - [j70]Matteo Riondato, Eli Upfal:
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. ACM Trans. Knowl. Discov. Data 12(5): 61:1-61:38 (2018) - [c121]Megumi Ando, Anna Lysyanskaya, Eli Upfal:
Practical and Provably Secure Onion Routing. ICALP 2018: 144:1-144:14 - [c120]Carsten Binnig, Benedetto Buratti, Yeounoh Chung, Cyrus Cousins, Tim Kraska, Zeyuan Shang, Eli Upfal, Robert C. Zeleznik, Emanuel Zgraggen:
Towards Interactive Curation & Automatic Tuning of ML Pipelines. DEEM@SIGMOD 2018: 1:1-1:4 - [c119]Morteza Chalabi Hajkarim, Eli Upfal, Fabio Vandin:
Differentially Mutated Subnetworks Discovery. WABI 2018: 18:1-18:14 - [i33]Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier M. Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir V. Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemyslaw Karpinski, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark S. Neubauer, Harvey B. Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel N. Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Andrew Stewart, Bob Stienen, Ian Stockdale, Giles Chatham Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata:
Machine Learning in High Energy Physics Community White Paper. CoRR abs/1807.02876 (2018) - [i32]Yeounoh Chung, Peter J. Haas, Eli Upfal, Tim Kraska:
Unknown Examples & Machine Learning Model Generalization. CoRR abs/1808.08294 (2018) - [i31]Lorenzo De Stefani, Leonhard F. Spiegelberg, Tim Kraska, Eli Upfal:
VizRec: A framework for secure data exploration via visual representation. CoRR abs/1811.00602 (2018) - [i30]Clayton Sanford, Cyrus Cousins, Eli Upfal:
Uniform Convergence Bounds for Codec Selection. CoRR abs/1812.07568 (2018) - 2017
- [j69]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
MapReduce and Streaming Algorithms for Diversity Maximization in Metric Spaces of Bounded Doubling Dimension. Proc. VLDB Endow. 10(5): 469-480 (2017) - [j68]Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal:
TRIÈST: Counting Local and Global Triangles in Fully Dynamic Streams with Fixed Memory Size. ACM Trans. Knowl. Discov. Data 11(4): 43:1-43:50 (2017) - [c118]Alessandro Epasto, Ahmad Mahmoody, Eli Upfal:
Real-Time Targeted-Influence Queries over Large Graphs. ASONAM 2017: 224-231 - [c117]Lorenzo De Stefani, Erisa Terolli, Eli Upfal:
Tiered sampling: An efficient method for approximate counting sparse motifs in massive graph streams. IEEE BigData 2017: 776-786 - [c116]Carsten Binnig, Fuat Basik, Benedetto Buratti, Ugur Çetintemel, Yeounoh Chung, Andrew Crotty, Cyrus Cousins, Dylan Ebert, Philipp Eichmann, Alex Galakatos, Benjamin Hättasch, Amir Ilkhechi, Tim Kraska, Zeyuan Shang, Isabella Tromba, Arif Usta, Prasetya Ajie Utama, Eli Upfal, Linnan Wang, Nathaniel Weir, Robert C. Zeleznik, Emanuel Zgraggen:
Towards Interactive Data Exploration. BIRTE (Revised Selected Papers) 2017: 177-190 - [c115]Carsten Binnig, Lorenzo De Stefani, Tim Kraska, Eli Upfal, Emanuel Zgraggen, Zheguang Zhao:
Toward Sustainable Insights, or Why Polygamy is Bad for You. CIDR 2017 - [c114]Cyrus Cousins, Eli Upfal:
The k-Nearest Representatives Classifier: A Distance-Based Classifier with Strong Generalization Bounds. DSAA 2017: 1-10 - [c113]Megumi Ando, Eli Upfal:
Minimizing operational cost for zero information leakage. ICC 2017: 1-7 - [c112]Zheguang Zhao, Lorenzo De Stefani, Emanuel Zgraggen, Carsten Binnig, Eli Upfal, Tim Kraska:
Controlling False Discoveries During Interactive Data Exploration. SIGMOD Conference 2017: 527-540 - [c111]Zheguang Zhao, Emanuel Zgraggen, Lorenzo De Stefani, Carsten Binnig, Eli Upfal, Tim Kraska:
Safe Visual Data Exploration. SIGMOD Conference 2017: 1671-1674 - [i29]Megumi Ando, Anna Lysyanskaya, Eli Upfal:
Scalable and Provably Secure P2P Communication Protocols. CoRR abs/1706.05367 (2017) - [i28]Lorenzo De Stefani, Erisa Terolli, Eli Upfal:
Tiered Sampling: An Efficient Method for Approximate Counting Sparse Motifs in Massive Graph Streams. CoRR abs/1710.02108 (2017) - [i27]Bodo Manthey, Claire Mathieu, Heiko Röglin, Eli Upfal:
Probabilistic Methods in the Design and Analysis of Algorithms (Dagstuhl Seminar 17141). Dagstuhl Reports 7(4): 1-22 (2017) - 2016
- [j67]Fabio Vandin, Benjamin J. Raphael, Eli Upfal:
On the Sample Complexity of Cancer Pathways Identification. J. Comput. Biol. 23(1): 30-41 (2016) - [c110]Lorenzo De Stefani, Alessandro Epasto, Eli Upfal, Fabio Vandin:
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic. AAAI 2016: 1526-1532 - [c109]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
A Practical Parallel Algorithm for Diameter Approximation of Massive Weighted Graphs. IPDPS 2016: 12-21 - [c108]Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal:
TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. KDD 2016: 825-834 - [c107]Matteo Riondato, Eli Upfal:
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. KDD 2016: 1145-1154 - [c106]Ahmad Mahmoody, Charalampos E. Tsourakakis, Eli Upfal:
Scalable Betweenness Centrality Maximization via Sampling. KDD 2016: 1765-1773 - [c105]John Augustine, William K. Moses Jr., Amanda Redlich, Eli Upfal:
Balanced Allocation: Patience is not a Virtue. SODA 2016: 655-671 - [c104]Ahmad Mahmoody, Matteo Riondato, Eli Upfal:
Wiggins: Detecting Valuable Information in Dynamic Networks Using Limited Resources. WSDM 2016: 677-686 - [i26]Matteo Riondato, Eli Upfal:
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. CoRR abs/1602.05866 (2016) - [i25]Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal:
TRIÈST: Counting Local and Global Triangles in Fully-dynamic Streams with Fixed Memory Size. CoRR abs/1602.07424 (2016) - [i24]John Augustine, William K. Moses Jr., Amanda Redlich, Eli Upfal:
Balanced Allocation: Patience is not a Virtue. CoRR abs/1602.08298 (2016) - [i23]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
MapReduce and Streaming Algorithms for Diversity Maximization in Metric Spaces of Bounded Doubling Dimension. CoRR abs/1605.05590 (2016) - [i22]Ahmad Mahmoody, Charalampos E. Tsourakakis, Eli Upfal:
Scalable Betweenness Centrality Maximization via Sampling. CoRR abs/1609.00790 (2016) - [i21]Zheguang Zhao, Lorenzo De Stefani, Emanuel Zgraggen, Carsten Binnig, Eli Upfal, Tim Kraska:
Controlling False Discoveries During Interactive Data Exploration. CoRR abs/1612.01040 (2016) - 2015
- [j66]John Augustine, Gopal Pandurangan, Peter Robinson, Eli Upfal:
Distributed agreement in dynamic peer-to-peer networks. J. Comput. Syst. Sci. 81(7): 1088-1109 (2015) - [j65]Fabio Vandin, Alexandra Papoutsaki, Benjamin J. Raphael, Eli Upfal:
Accurate Computation of Survival Statistics in Genome-Wide Studies. PLoS Comput. Biol. 11(5) (2015) - [j64]Atish Das Sarma, Anisur Rahaman Molla, Gopal Pandurangan, Eli Upfal:
Fast distributed PageRank computation. Theor. Comput. Sci. 561: 113-121 (2015) - [c103]Ahmad Mahmoody, Evgenios M. Kornaropoulos, Eli Upfal:
Optimizing Static and Adaptive Probing Schedules for Rapid Event Detection. COCOA 2015: 377-391 - [c102]Guru Prakash Arumugam, Prashanth Srikanthan, John Augustine, Krishna V. Palem, Eli Upfal, Ayush Bhargava, Parishkrati, Sreelatha Yenugula:
Novel inexact memory aware algorithm co-design for energy efficient computation: algorithmic principles. DATE 2015: 752-757 - [c101]John Augustine, Gopal Pandurangan, Peter Robinson, Scott T. Roche, Eli Upfal:
Enabling Robust and Efficient Distributed Computation in Dynamic Peer-to-Peer Networks. FOCS 2015: 350-369 - [c100]Matteo Riondato, Eli Upfal:
Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages. KDD 2015: 1005-1014 - [c99]Matteo Riondato, Eli Upfal:
VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms. KDD 2015: 2321-2322 - [c98]Fabio Vandin, Benjamin J. Raphael, Eli Upfal:
On the Sample Complexity of Cancer Pathways Identification. RECOMB 2015: 326-337 - [c97]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
Space and Time Efficient Parallel Graph Decomposition, Clustering, and Diameter Approximation. SPAA 2015: 182-191 - [i20]Ahmad Mahmoody, Eli Upfal:
The Probabilistic Hitting Set Paradigm: a General Framework for Search and Detection in Dynamic Social Networks. CoRR abs/1504.03275 (2015) - [i19]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
A Practical Parallel Algorithm for Diameter Approximation of Massive Weighted Graphs. CoRR abs/1506.03265 (2015) - [i18]Ahmad Mahmoody, Evgenios M. Kornaropoulos, Eli Upfal:
Optimizing Static and Adaptive Probing Schedules for Rapid Event Detection. CoRR abs/1509.02487 (2015) - 2014
- [j63]Matteo Riondato, Eli Upfal:
Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees. ACM Trans. Knowl. Discov. Data 8(4): 20:1-20:32 (2014) - [c96]Jennie Duggan, Olga Papaemmanouil, Ugur Çetintemel, Eli Upfal:
Contender: A Resource Modeling Approach for Concurrent Query Performance Prediction. EDBT 2014: 109-120 - [c95]Olga Ohrimenko, Michael T. Goodrich, Roberto Tamassia, Eli Upfal:
The Melbourne Shuffle: Improving Oblivious Storage in the Cloud. ICALP (2) 2014: 556-567 - [p1]Michael Mitzenmacher, Eli Upfal:
Some Practical Randomized Algorithms and Data Structures. Computing Handbook, 3rd ed. (1) 2014: 11: 1-23 - [i17]Olga Ohrimenko, Michael T. Goodrich, Roberto Tamassia, Eli Upfal:
The Melbourne Shuffle: Improving Oblivious Storage in the Cloud. CoRR abs/1402.5524 (2014) - [i16]Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci, Eli Upfal:
Parallel Graph Decomposition and Diameter Approximation in o(Diameter) Time and Linear Space. CoRR abs/1407.3144 (2014) - 2013
- [c94]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Identifying significant mutations in large cohorts of cancer genomes. ICCABS 2013: 1 - [c93]Atish Das Sarma, Anisur Rahaman Molla, Gopal Pandurangan, Eli Upfal:
Fast Distributed PageRank Computation. ICDCN 2013: 11-26 - [c92]Fabio Vandin, Alexandra Papoutsaki, Benjamin J. Raphael, Eli Upfal:
Genome-Wide Survival Analysis of Somatic Mutations in Cancer. RECOMB 2013: 285-286 - [c91]John Augustine, Anisur Rahaman Molla, Ehab Morsy, Gopal Pandurangan, Peter Robinson, Eli Upfal:
Storage and search in dynamic peer-to-peer networks. SPAA 2013: 53-62 - [e2]Hubertus Franke, Alexander Heinecke, Krishna V. Palem, Eli Upfal:
Computing Frontiers Conference, CF'13, Ischia, Italy, May 14 - 16, 2013. ACM 2013, ISBN 978-1-4503-2053-5 [contents] - [i15]Milos Hauskrecht, Eli Upfal:
A Clustering Approach to Solving Large Stochastic Matching Problems. CoRR abs/1301.2277 (2013) - [i14]John Augustine, Anisur Rahaman Molla, Ehab Morsy, Gopal Pandurangan, Peter Robinson, Eli Upfal:
Storage and Search in Dynamic Peer-to-Peer Networks. CoRR abs/1305.1121 (2013) - [i13]Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal:
Bandits and Experts in Metric Spaces. CoRR abs/1312.1277 (2013) - 2012
- [j62]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Finding Driver Pathways in Cancer: Models and Algorithms. Algorithms Mol. Biol. 7: 23 (2012) - [j61]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Algorithms and Genome Sequencing: Identifying Driver Pathways in Cancer. Computer 45(3): 39-46 (2012) - [j60]Adam Kirsch, Michael Mitzenmacher, Andrea Pietracaprina, Geppino Pucci, Eli Upfal, Fabio Vandin:
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets. J. ACM 59(3): 12:1-12:22 (2012) - [c90]Matteo Riondato, Justin A. DeBrabant, Rodrigo Fonseca, Eli Upfal:
PARMA: a parallel randomized algorithm for approximate association rules mining in MapReduce. CIKM 2012: 85-94 - [c89]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Workshop: Algorithms for discovery of mutated pathways in cancer. ICCABS 2012: 1 - [c88]Mert Akdere, Ugur Çetintemel, Matteo Riondato, Eli Upfal, Stanley B. Zdonik:
Learning-based Query Performance Modeling and Prediction. ICDE 2012: 390-401 - [c87]Andrea Pietracaprina, Geppino Pucci, Matteo Riondato, Francesco Silvestri, Eli Upfal:
Space-round tradeoffs for MapReduce computations. ICS 2012: 235-244 - [c86]Aris Anagnostopoulos, Ravi Kumar, Mohammad Mahdian, Eli Upfal, Fabio Vandin:
Algorithms on evolving graphs. ITCS 2012: 149-160 - [c85]Bahman Bahmani, Ravi Kumar, Mohammad Mahdian, Eli Upfal:
PageRank on an evolving graph. KDD 2012: 24-32 - [c84]Matteo Riondato, Eli Upfal:
Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees. ECML/PKDD (1) 2012: 25-41 - [c83]Fabio Vandin, Patrick Clay, Eli Upfal, Benjamin J. Raphael:
Discovery of Mutated Subnetworks Associated with Clinical Data in Cancer. Pacific Symposium on Biocomputing 2012: 55-66 - [c82]John Augustine, Gopal Pandurangan, Peter Robinson, Eli Upfal:
Towards robust and efficient computation in dynamic peer-to-peer networks. SODA 2012: 551-569 - [i12]Atish Das Sarma, Anisur Rahaman Molla, Gopal Pandurangan, Eli Upfal:
Fast Distributed PageRank Computation. CoRR abs/1208.3071 (2012) - 2011
- [j59]Fabio Vandin, Eli Upfal, Benjamin J. Raphael:
Algorithms for Detecting Significantly Mutated Pathways in Cancer. J. Comput. Biol. 18(3): 507-522 (2011) - [j58]Roberto Grossi, Andrea Pietracaprina, Nadia Pisanti, Geppino Pucci, Eli Upfal, Fabio Vandin:
MADMX: A Strategy for Maximal Dense Motif Extraction. J. Comput. Biol. 18(4): 535-545 (2011) - [j57]Aris Anagnostopoulos, Ravi Kumar, Mohammad Mahdian, Eli Upfal:
Sorting and selection on dynamic data. Theor. Comput. Sci. 412(24): 2564-2576 (2011) - [c81]