| 2025 | CPAIOR | LLMs for Cold-Start Cutting Plane Separator Configuration. | Connor Lawless, Yingxi Li, Anders Wikum, Madeleine Udell, Ellen Vitercik |
| 2025 | ICML | Primal-Dual Neural Algorithmic Reasoning. | Yu He, Ellen Vitercik |
| 2025 | ICML | Algorithms with Calibrated Machine Learning Predictions. | Judy Hanwen Shen, Ellen Vitercik, Anders Wikum |
| 2025 | ICML | Wait-Less Offline Tuning and Re-solving for Online Decision Making. | Jingruo Sun, Wenzhi Gao, Ellen Vitercik, Yinyu Ye |
| 2025 | ICML | EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations. | Haotian Zhai, Connor Lawless, Ellen Vitercik, Liu Leqi |
| 2025 | IJCAI | New Sequence-Independent Lifting Techniques for Cover Inequalities and When They Induce Facets. | Siddharth Prasad, Ellen Vitercik, Maria-Florina Balcan, Tuomas Sandholm |
| 2024 | ICML | MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation. | Alexandre Hayderi, Amin Saberi, Ellen Vitercik, Anders Wikum |
| 2022 | CP | Improved Sample Complexity Bounds for Branch-And-Cut. | Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik |
| 2022 | ICML | No-Regret Learning in Partially-Informed Auctions. | Wenshuo Guo, Michael I. Jordan, Ellen Vitercik |
| 2021 | AAAI | Generalization in Portfolio-Based Algorithm Selection. | Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik |
| 2021 | AISTATS | Private optimization without constraint violations. | Andrs Muoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik |
| 2021 | STOC | How much data is sufficient to learn high-performing algorithms? generalization guarantees for data-driven algorithm design. | Maria-Florina Balcan, Dan F. DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm, Ellen Vitercik |
| 2020 | AAAI | Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees. | Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik |
| 2020 | ICML | Refined bounds for algorithm configuration: The knife-edge of dual class approximability. | Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik |
| 2019 | AIES | Algorithmic Greenlining: An Approach to Increase Diversity. | Christian Borgs, Jennifer T. Chayes, Nika Haghtalab, Adam Tauman Kalai, Ellen Vitercik |
| 2019 | COLT | Learning to Prune: Speeding up Repeated Computations. | Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik |
| 2019 | EC | Estimating Approximate Incentive Compatibility. | Maria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik |
| 2018 | FOCS | Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization. | Maria-Florina Balcan, Travis Dick, Ellen Vitercik |
| 2018 | ICALP | Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions. | Bernhard Haeupler, Amirbehshad Shahrasbi, Ellen Vitercik |
| 2018 | ICML | Learning to Branch. | Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, Ellen Vitercik |
| 2017 | COLT | Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems. | Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White |
| 2016 | COLT | Learning Combinatorial Functions from Pairwise Comparisons. | Maria-Florina Balcan, Ellen Vitercik, Colin White |