Eric Balkanski

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 56

Top Topics

Convex Minimization

Mechanism Design

Top Venues

Publications

Eric Balkanski, Noémie Périvier, Clifford Stein, Hao-Ting Wei
Energy-Efficient Scheduling with Predictions. CoRR (2024)
Eric Balkanski, Steven DiSilvio, Alan Kuhnle
Submodular Maximization in Exactly n Queries. CoRR (2024)
Eric Balkanski, Christopher En, Yuri Faenza
An Algorithm for the Assignment Game Beyond Additive Valuations. CoRR (2024)
Eric Balkanski, Yuri Faenza, Mathieu Kubik
The simultaneous semi-random model for TSP. Math. Program. 206 (1) (2024)
Eric Balkanski, Tingting Ou, Clifford Stein, Hao-Ting Wei
Scheduling with Speed Predictions. WAOA (2023)
Eric Balkanski, Vasilis Gkatzelis, Xizhi Tan
Strategyproof Scheduling with Predictions. ITCS (2023)
Eric Balkanski, Vasilis Gkatzelis, Xizhi Tan, Cherlin Zhu
Online Mechanism Design with Predictions. CoRR (2023)
Arpit Agarwal, Eric Balkanski
Learning-Augmented Dynamic Submodular Maximization. CoRR (2023)
Eric Balkanski, Noémie Périvier, Clifford Stein, Hao-Ting Wei
Energy-Efficient Scheduling with Predictions. NeurIPS (2023)
Eric Balkanski, Yuri Faenza, Noémie Périvier
The Power of Greedy for Online Minimum Cost Matching on the Line. EC (2023)
Eric Balkanski, Yuri Faenza, Noémie Périvier
The Power of Greedy for Online Minimum Cost Matching on the Line. CoRR (2022)
Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. CoRR (2022)
Eric Balkanski, Oussama Hanguir, Shatian Wang
Learning Low Degree Hypergraphs. COLT (2022)
Eric Balkanski, Vasilis Gkatzelis, Xizhi Tan
Strategyproof Scheduling with Predictions. CoRR (2022)
Eric Balkanski, Yuri Faenza, Mathieu Kubik
The Simultaneous Semi-random Model for TSP. IPCO (2022)
Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, Xizhi Tan
Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location. EC (2022)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
The Limitations of Optimization from Samples. J. ACM 69 (3) (2022)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
An Optimal Approximation for Submodular Maximization Under a Matroid Constraint in the Adaptive Complexity Model. Oper. Res. 70 (5) (2022)
Eric Balkanski, Pranav Garimidi, Vasilis Gkatzelis, Daniel Schoepflin, Xizhi Tan
Deterministic Budget-Feasible Clock Auctions. SODA (2022)
Eric Balkanski, Oussama Hanguir, Shatian Wang
Learning Low Degree Hypergraphs. CoRR (2022)
Eric Balkanski, Tingting Ou, Clifford Stein, Hao-Ting Wei
Scheduling with Speed Predictions. CoRR (2022)
Eric Balkanski, Sharon Qian, Yaron Singer
Instance Specific Approximations for Submodular Maximization. CoRR (2021)
Eric Balkanski, Pranav Garimidi, Vasilis Gkatzelis, Daniel Schoepflin, Xizhi Tan
Deterministic Budget-Feasible Clock Auctions. CoRR (2021)
Eric Balkanski, Sharon Qian, Yaron Singer
Instance Specific Approximations for Submodular Maximization. ICML (2021)
Shipra Agrawal, Eric Balkanski, Vahab S. Mirrokni, Balasubramanian Sivan
Robust Repeated First Price Auctions. EC (2021)
Eric Balkanski, Yaron Singer
A lower bound for parallel submodular minimization. STOC (2020)
Eric Balkanski, Renato Paes Leme
On the Construction of Substitutes. Math. Oper. Res. 45 (1) (2020)
Adam Breuer, Eric Balkanski, Yaron Singer
The FAST Algorithm for Submodular Maximization. ICML (2020)
Ron Kupfer, Sharon Qian, Eric Balkanski, Yaron Singer
The Adaptive Complexity of Maximizing a Gross Substitutes Valuation. NeurIPS (2020)
Eric Balkanski, Harrison Chase, Kojin Oshiba, Alexander Rilee, Yaron Singer, Richard Wang
Adversarial Attacks on Binary Image Recognition Systems. CoRR (2020)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
An Exponential Speedup in Parallel Running Time for Submodular Maximization without Loss in Approximation. SODA (2019)
Sepehr Assadi, Eric Balkanski, Renato Paes Leme
Secretary Ranking with Minimal Inversions. NeurIPS (2019)
Shipra Agrawal, Eric Balkanski, Vahab S. Mirrokni, Balasubramanian Sivan
Dynamic First Price Auctions Robust to Heterogeneous Buyers. CoRR (2019)
Adam Breuer, Eric Balkanski, Yaron Singer
The FAST Algorithm for Submodular Maximization. CoRR (2019)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
An optimal approximation for submodular maximization under a matroid constraint in the adaptive complexity model. STOC (2019)
Eric Balkanski, Adam Breuer, Yaron Singer
Non-monotone Submodular Maximization in Exponentially Fewer Iterations. CoRR (2018)
Eric Balkanski, Nicole Immorlica, Yaron Singer
The Importance of Communities for Learning to Influence. CoRR (2018)
Eric Balkanski, Adam Breuer, Yaron Singer
Non-monotone Submodular Maximization in Exponentially Fewer Iterations. NeurIPS (2018)
Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer
Learning to Optimize Combinatorial Functions. ICML (2018)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
An Exponential Speedup in Parallel Running Time for Submodular Maximization without Loss in Approximation. CoRR (2018)
Eric Balkanski, Renato Paes Leme
On the Construction of Substitutes. EC (2018)
Eric Balkanski, Yaron Singer
The adaptive complexity of maximizing a submodular function. STOC (2018)
Eric Balkanski, Yaron Singer
Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization. CoRR (2018)
Eric Balkanski, Yaron Singer
Approximation Guarantees for Adaptive Sampling. ICML (2018)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
An Optimal Approximation for Submodular Maximization under a Matroid Constraint in the Adaptive Complexity Model. CoRR (2018)
Sepehr Assadi, Eric Balkanski, Renato Paes Leme
Secretary Ranking with Minimal Inversions. CoRR (2018)
Eric Balkanski, Renato Paes Leme
On the Construction of Substitutes. CoRR (2018)
Eric Balkanski, Umar Syed, Sergei Vassilvitskii
Statistical Cost Sharing. CoRR (2017)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
The limitations of optimization from samples. STOC (2017)
Eric Balkanski, Nicole Immorlica, Yaron Singer
The Importance of Communities for Learning to Influence. NIPS (2017)
Eric Balkanski, Yaron Singer
The Sample Complexity of Optimizing a Convex Function. COLT (2017)
Eric Balkanski, Umar Syed, Sergei Vassilvitskii
Statistical Cost Sharing. NIPS (2017)
Eric Balkanski, Yaron Singer
Minimizing a Submodular Function from Samples. NIPS (2017)
Eric Balkanski, Jason D. Hartline
Bayesian Budget Feasibility with Posted Pricing. WWW (2016)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
The Power of Optimization from Samples. NIPS (2016)
Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. ICML (2016)
Eric Balkanski, Francine Blanchet-Sadri, Matthew Kilgore, Benjamin J. Wyatt
On the state complexity of partial word DFAs. Theor. Comput. Sci. 578 (2015)
Eric Balkanski, Aviad Rubinstein, Yaron Singer
The Limitations of Optimization from Samples. CoRR (2015)
Eric Balkanski, Jason D. Hartline
Bayesian Budget Feasibility with Posted Pricing. CoRR (2015)
Eric Balkanski, Yaron Singer
Mechanisms for Fair Attribution. EC (2015)
Eric Balkanski, Simina Brânzei, David Kurokawa, Ariel D. Procaccia
Simultaneous Cake Cutting. AAAI (2014)
Eric Balkanski, Francine Blanchet-Sadri, Matthew Kilgore, Benjamin J. Wyatt
Partial Word DFAs. CIAA (2013)