Ellen Vitercik

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 50

Top Topics

Sample Complexity

Top Venues

Publications

Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik
Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization. J. ACM 71 (2) (2024)
Alexandre Hayderi, Amin Saberi, Ellen Vitercik, Anders Wikum
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation. CoRR (2024)
Vaggos Chatziafratis, Ishani Karmarkar, Ellen Vitercik
From Large to Small Datasets: Size Generalization for Clustering Algorithm Selection. CoRR (2024)
Joon Suk Huh, Ellen Vitercik, Kirthevasan Kandasamy
Bandit Profit-maximization for Targeted Marketing. CoRR (2024)
Siddharth Prasad, Ellen Vitercik, Maria-Florina Balcan, Tuomas Sandholm
New Sequence-Independent Lifting Techniques for Cutting Planes and When They Induce Facets. CoRR (2024)
Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. EC (2023)
Christian Borgs, Jennifer T. Chayes, Christian Ikeokwu, Ellen Vitercik
Disincentivizing Polarization in Social Networks. CoRR (2023)
Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, Ellen Vitercik
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty. CoRR (2023)
Ellen Vitercik, Manolis Zampetakis, David Zhang
Sorting from Crowdsourced Comparisons using Expert Verifications. CoRR (2023)
Christian Borgs, Jennifer T. Chayes, Christian Ikeokwu, Ellen Vitercik
Disincentivizing Polarization in Social Networks. AiOfAi@IJCAI (2023)
Kiriaki Frangias, Andrew Lin, Ellen Vitercik, Manolis Zampetakis
Algorithmic Contract Design for Crowdsourced Ranking. CoRR (2023)
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Improved Sample Complexity Bounds for Branch-And-Cut. CP (2022)
Wenshuo Guo, Michael I. Jordan, Ellen Vitercik
No-Regret Learning in Partially-Informed Auctions. CoRR (2022)
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts. NeurIPS (2022)
Wenshuo Guo, Michael I. Jordan, Ellen Vitercik
No-Regret Learning in Partially-Informed Auctions. ICML (2022)
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts. CoRR (2022)
Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik
Private optimization without constraint violations. AISTATS (2021)
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond. CoRR (2021)
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond. NeurIPS (2021)
Ellen Vitercik, Tom Yan
Revenue maximization via machine learning with noisy data. NeurIPS (2021)
Maria-Florina Balcan, Dan F. DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm, Ellen Vitercik
How much data is sufficient to learn high-performing algorithms? generalization guarantees for data-driven algorithm design. STOC (2021)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Generalization in Portfolio-Based Algorithm Selection. AAAI (2021)
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
Improved Learning Bounds for Branch-and-Cut. CoRR (2021)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees. AAAI (2020)
Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik
Private Optimization Without Constraint Violations. CoRR (2020)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Refined bounds for algorithm configuration: The knife-edge of dual class approximability. CoRR (2020)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Refined bounds for algorithm configuration: The knife-edge of dual class approximability. ICML (2020)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Generalization in portfolio-based algorithm selection. CoRR (2020)
Maria-Florina Balcan, Dan F. DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm, Ellen Vitercik
How much data is sufficient to learn high-performing algorithms? CoRR (2019)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Estimating Approximate Incentive Compatibility. CoRR (2019)
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
Learning to Prune: Speeding up Repeated Computations. CoRR (2019)
Christian Borgs, Jennifer T. Chayes, Nika Haghtalab, Adam Tauman Kalai, Ellen Vitercik
Algorithmic Greenlining: An Approach to Increase Diversity. AIES (2019)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees. CoRR (2019)
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
Learning to Prune: Speeding up Repeated Computations. COLT (2019)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Estimating Approximate Incentive Compatibility. EC (2019)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
A General Theory of Sample Complexity for Multi-Item Profit Maximization. EC (2018)
Maria-Florina Balcan, Travis Dick, Ellen Vitercik
Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization. FOCS (2018)
Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik
Learning to Branch. CoRR (2018)
Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik
Learning to Branch. ICML (2018)
Bernhard Haeupler, Amirbehshad Shahrasbi, Ellen Vitercik
Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions. ICALP (2018)
Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems. COLT (2017)
Maria-Florina Balcan, Travis Dick, Ellen Vitercik
Private and Online Optimization of Piecewise Lipschitz Functions. CoRR (2017)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Sample Complexity of Multi-Item Profit Maximization. CoRR (2017)
Bernhard Haeupler, Amirbehshad Shahrasbi, Ellen Vitercik
Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions. CoRR (2017)
Maria-Florina Balcan, Ellen Vitercik, Colin White
Learning Combinatorial Functions from Pairwise Comparisons. COLT (2016)
Casey Mann, Joseph DiNatale, Emily Peirce, Ellen Vitercik
Unilateral and equitransitive tilings by squares of four sizes. Ars Math. Contemp. 10 (1) (2016)
Maria-Florina Balcan, Ellen Vitercik, Colin White
Learning Combinatorial Functions from Pairwise Comparisons. CoRR (2016)
Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White
Learning the best algorithm for max-cut, clustering, and other partitioning problems. CoRR (2016)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Sample Complexity of Automated Mechanism Design. NIPS (2016)
Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik
Sample Complexity of Automated Mechanism Design. CoRR (2016)
Allison B. Lewko, Ellen Vitercik
Balancing Communication for Multi-party Interactive Coding. CoRR (2015)