Partial Word DFAs. - Eric Balkanski; Francine Blanchet-Sadri; Matthew Kilgore; Benjamin J. Wyatt (CIAA, 2013)

Simultaneous Cake Cutting. - Eric Balkanski; Simina Brânzei; David Kurokawa; Ariel D. Procaccia (AAAI, 2014)

Mechanisms for Fair Attribution. - Eric Balkanski; Yaron Singer (EC, 2015)

On the state complexity of partial word DFAs. - Eric Balkanski; Francine Blanchet-Sadri; Matthew Kilgore; Benjamin J. Wyatt (Theor. Comput. Sci., 2015)

Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. - Eric Balkanski; Baharan Mirzasoleiman; Andreas Krause 001; Yaron Singer (ICML, 2016)

The Power of Optimization from Samples. - Eric Balkanski; Aviad Rubinstein; Yaron Singer (NIPS, 2016)

Bayesian Budget Feasibility with Posted Pricing. - Eric Balkanski; Jason D. Hartline (WWW, 2016)

The Sample Complexity of Optimizing a Convex Function. - Eric Balkanski; Yaron Singer (COLT, 2017)

The Importance of Communities for Learning to Influence. - Eric Balkanski; Nicole Immorlica; Yaron Singer (NIPS, 2017)

Minimizing a Submodular Function from Samples. - Eric Balkanski; Yaron Singer (NIPS, 2017)

Statistical Cost Sharing. - Eric Balkanski; Umar Syed; Sergei Vassilvitskii (NIPS, 2017)

Approximation Guarantees for Adaptive Sampling. - Eric Balkanski; Yaron Singer (ICML, 2018)

Learning to Optimize Combinatorial Functions. - Nir Rosenfeld; Eric Balkanski; Amir Globerson; Yaron Singer (ICML, 2018)

Non-monotone Submodular Maximization in Exponentially Fewer Iterations. - Eric Balkanski; Adam Breuer; Yaron Singer (NeurIPS, 2018)

The adaptive complexity of maximizing a submodular function. - Eric Balkanski; Yaron Singer (STOC, 2018)

Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization. - Eric Balkanski; Yaron Singer (CoRR, 2018)

Secretary Ranking with Minimal Inversions. - Sepehr Assadi; Eric Balkanski; Renato Paes Leme (NeurIPS, 2019)

An Exponential Speedup in Parallel Running Time for Submodular Maximization without Loss in Approximation. - Eric Balkanski; Aviad Rubinstein; Yaron Singer (SODA, 2019)

Dynamic First Price Auctions Robust to Heterogeneous Buyers. - Shipra Agrawal 001; Eric Balkanski; Vahab S. Mirrokni; Balasubramanian Sivan (CoRR, 2019)

The FAST Algorithm for Submodular Maximization. - Adam Breuer; Eric Balkanski; Yaron Singer (ICML, 2020)

The Adaptive Complexity of Maximizing a Gross Substitutes Valuation. - Ron Kupfer; Sharon Qian; Eric Balkanski; Yaron Singer (NeurIPS, 2020)

A lower bound for parallel submodular minimization. - Eric Balkanski; Yaron Singer (STOC, 2020)

Adversarial Attacks on Binary Image Recognition Systems. - Eric Balkanski; Harrison Chase; Kojin Oshiba; Alexander Rilee; Yaron Singer; Richard Wang (CoRR, 2020)

On the Construction of Substitutes. - Eric Balkanski; Renato Paes Leme (Math. Oper. Res., 2020)

Instance Specific Approximations for Submodular Maximization. - Eric Balkanski; Sharon Qian; Yaron Singer (ICML, 2021)

Robust Repeated First Price Auctions. - Shipra Agrawal 001; Eric Balkanski; Vahab S. Mirrokni; Balasubramanian Sivan (EC, 2021)

Learning Low Degree Hypergraphs. - Eric Balkanski; Oussama Hanguir; Shatian Wang (COLT, 2022)

Deterministic Budget-Feasible Clock Auctions. - Eric Balkanski; Pranav Garimidi; Vasilis Gkatzelis; Daniel Schoepflin 001; Xizhi Tan (SODA, 2022)

An Optimal Approximation for Submodular Maximization Under a Matroid Constraint in the Adaptive Complexity Model. - Eric Balkanski; Aviad Rubinstein; Yaron Singer (Oper. Res., 2022)

The Limitations of Optimization from Samples. - Eric Balkanski; Aviad Rubinstein; Yaron Singer (J. ACM, 2022)

Strategyproof Scheduling with Predictions. - Eric Balkanski; Vasilis Gkatzelis; Xizhi Tan (ITCS, 2023)

Energy-Efficient Scheduling with Predictions. - Eric Balkanski; Noémie Périvier; Clifford Stein 001; Hao-Ting Wei (NeurIPS, 2023)

The Power of Greedy for Online Minimum Cost Matching on the Line. - Eric Balkanski; Yuri Faenza; Noémie Périvier (EC, 2023)

Mechanism Design with Predictions: An Annotated Reading List. - Eric Balkanski; Vasilis Gkatzelis; Xizhi Tan (SIGecom Exch., 2023)

Learning-Augmented Dynamic Submodular Maximization. - Arpit Agarwal; Eric Balkanski (NeurIPS, 2024)

Randomized Strategic Facility Location with Predictions. - Eric Balkanski; Vasilis Gkatzelis; Golnoosh Shahkarami (NeurIPS, 2024)

Fair Secretaries with Unfair Predictions. - Eric Balkanski; Will Ma; Andreas Maggiori (NeurIPS, 2024)

An Algorithm for the Assignment Game Beyond Additive Valuations. - Eric Balkanski; Christopher En; Yuri Faenza (EC, 2024)

Online Mechanism Design with Predictions. - Eric Balkanski; Vasilis Gkatzelis; Xizhi Tan; Cherlin Zhu (EC, 2024)

Submodular Maximization in Exactly n Queries. - Eric Balkanski; Steven DiSilvio; Alan Kuhnle (CoRR, 2024)

Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. - Priyank Agrawal; Eric Balkanski; Vasilis Gkatzelis; Tingting Ou; Xizhi Tan (Math. Oper. Res., 2024)

The simultaneous semi-random model for TSP. - Eric Balkanski; Yuri Faenza; Mathieu Kubik (Math. Program., 2024)

Cost-Free Fairness in Online Correlation Clustering. - Eric Balkanski; Jason Chatzitheodorou; Andreas Maggiori (ALT, 2025)

Strategyproof Learning with Advice. - Eric Balkanski; Cherlin Zhu (ALT, 2025)

Scheduling with Speed Predictions. - Eric Balkanski; Tingting Ou; Clifford Stein 001; Hao-Ting Wei (Theory Comput. Syst., 2025)