Playing Dominoes Is Hard, Except by Yourself. - Erik D. Demaine; Fermi Ma; Erik Waingarten (FUN, 2014)

Mario Kart Is Hard. - Jeffrey Bosboom; Erik D. Demaine; Adam Hesterberg; Jayson Lynch; Erik Waingarten (JCDCGG, 2015)

You Should Be Scared of German Ghost. - Erik D. Demaine; Fermi Ma; Matthew Susskind; Erik Waingarten (J. Inf. Process., 2015)

Lower Bounds on Time-Space Trade-Offs for Approximate Near Neighbors. - Alexandr Andoni; Thijs Laarhoven; Ilya P. Razenshteyn; Erik Waingarten (CoRR, 2016)

Approximate Near Neighbors for General Symmetric Norms. - Alexandr Andoni; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (CoRR, 2016)

Adaptivity Is Exponentially Powerful for Testing Monotonicity of Halfspaces. - Xi Chen 001; Rocco A. Servedio; Li-Yang Tan; Erik Waingarten (APPROX-RANDOM, 2017)

Boolean Unateness Testing with Õ(n3/4) Adaptive Queries. - Xi Chen 001; Erik Waingarten; Jinyu Xie (FOCS, 2017)

Optimal Hashing-based Time-Space Trade-offs for Approximate Near Neighbors. - Alexandr Andoni; Thijs Laarhoven; Ilya P. Razenshteyn; Erik Waingarten (SODA, 2017)

Approximate near neighbors for general symmetric norms. - Alexandr Andoni; Huy L. Nguyen; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (STOC, 2017)

Beyond Talagrand functions: new lower bounds for testing monotonicity and unateness. - Xi Chen 001; Erik Waingarten; Jinyu Xie (STOC, 2017)

Settling the query complexity of non-adaptive junta testing. - Xi Chen 001; Rocco A. Servedio; Li-Yang Tan; Erik Waingarten; Jinyu Xie (Electron. Colloquium Comput. Complex., 2017)

Arboral satisfaction: Recognition and LP approximation. - Erik D. Demaine; Varun Ganesan; Vladislav Kontsevoi; Qipeng Liu 001; Quanquan C. Liu; Fermi Ma; Ofir Nachum; Aaron Sidford; Erik Waingarten; Daniel Ziegler 002 (Inf. Process. Lett., 2017)

Hölder Homeomorphisms and Approximate Nearest Neighbors. - Alexandr Andoni; Assaf Naor; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (FOCS, 2018)

Data-dependent hashing via nonlinear spectral gaps. - Alexandr Andoni; Assaf Naor; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (STOC, 2018)

Lower Bounds for Tolerant Junta and Unateness Testing via Rejection Sampling of Graphs. - Amit Levi; Erik Waingarten (Electron. Colloquium Comput. Complex., 2018)

The fewest clues problem. - Erik D. Demaine; Fermi Ma; Ariel Schvartzman; Erik Waingarten; Scott Aaronson (Theor. Comput. Sci., 2018)

On Mean Estimation for General Norms with Statistical Queries. - Jerry Li 001; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (COLT, 2019)

Testing unateness nearly optimally. - Xi Chen 001; Erik Waingarten (STOC, 2019)

Optimal Adaptive Detection of Monotone Patterns. - Omri Ben-Eliezer; Shoham Letzter; Erik Waingarten (CoRR, 2019)

Finding monotone patterns in sublinear time. - Omri Ben-Eliezer; Clément L. Canonne; Shoham Letzter; Erik Waingarten (Electron. Colloquium Comput. Complex., 2019)

Random Restrictions of High-Dimensional Distributions and Uniformity Testing with Subcube Conditioning. - Clément L. Canonne; Xi Chen 001; Gautam Kamath 001; Amit Levi; Erik Waingarten (Electron. Colloquium Comput. Complex., 2019)

Approximating the Distance to Monotonicity of Boolean Functions. - Ramesh Krishnan S. Pallavoor; Sofya Raskhodnikova; Erik Waingarten (Electron. Colloquium Comput. Complex., 2019)

Nearly optimal edge estimation with independent set queries. - Xi Chen 001; Amit Levi; Erik Waingarten (SODA, 2020)

Learning and Testing Junta Distributions with Subcube Conditioning. - Xi Chen 001; Rajesh Jayaram; Amit Levi; Erik Waingarten (CoRR, 2020)

New Methods in Sublinear Computation for High Dimensional Problems. - Erik Alex Waingarten (2020)

Learning and testing junta distributions with sub cube conditioning. - Xi Chen 001; Rajesh Jayaram; Amit Levi; Erik Waingarten (COLT, 2021)

Approximate Nearest Neighbors Beyond Space Partitions. - Alexandr Andoni; Aleksandar Nikolov; Ilya P. Razenshteyn; Erik Waingarten (SODA, 2021)

Finding Monotone Patterns in Sublinear Time, Adaptively. - Omri Ben-Eliezer; Shoham Letzter; Erik Waingarten (ICALP, 2022)

Polylogarithmic Sketches for Clustering. - Moses Charikar; Erik Waingarten (ICALP, 2022)

Estimation of Entropy in Constant Space with Improved Sample Complexity. - Maryam Aliakbarpour; Andrew McGregor 001; Jelani Nelson; Erik Waingarten (NeurIPS, 2022)

New streaming algorithms for high dimensional EMD and MST. - Xi Chen 001; Rajesh Jayaram; Amit Levi; Erik Waingarten (STOC, 2022)

Fast Algorithms for a New Relaxation of Optimal Transport. - Moses Charikar; Beidi Chen; Christopher Ré; Erik Waingarten (COLT, 2023)

Near-Linear Time Algorithm for the Chamfer Distance. - Ainesh Bakshi; Piotr Indyk; Rajesh Jayaram; Sandeep Silwal; Erik Waingarten (NeurIPS, 2023)

Simple, Scalable and Effective Clustering via One-Dimensional Projections. - Moses Charikar; Monika Henzinger; Lunjia Hu; Maximilian Vötsch; Erik Waingarten (NeurIPS, 2023)

Streaming Euclidean MST to a Constant Factor. - Xi Chen 001; Vincent Cohen-Addad; Rajesh Jayaram; Amit Levi; Erik Waingarten (STOC, 2023)

A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. - Moses Charikar; Michael Kapralov; Erik Waingarten (SODA, 2024)

Data-Dependent LSH for the Earth Mover's Distance. - Rajesh Jayaram; Erik Waingarten; Tian Zhang (STOC, 2024)

Average-Distortion Sketching. - Yiqiao Bao; Anubhav Baweja; Nicolas Menand; Erik Waingarten; Nathan White; Tian Zhang (CoRR, 2024)

Lower Bounds for Convexity Testing. - Xi Chen 001; Anindya De; Shivam Nadimpalli; Rocco A. Servedio; Erik Waingarten (SODA, 2025)

Nearly Tight Bounds on Testing of Metric Properties. - Yiqiao Bao; Sampath Kannan; Erik Waingarten (SODA, 2025)

The Johnson-Lindenstrauss Lemma for Clustering and Subspace Approximation: From Coresets to Dimension Reduction. - Moses Charikar; Erik Waingarten (SODA, 2025)

Monotonicity Testing of High-Dimensional Distributions with Subcube Conditioning. - Deeparnab Chakrabarty; Xi Chen 001; Simeon Ristic; C. Seshadhri 001; Erik Waingarten (STOC, 2025)

Streaming and Massively Parallel Algorithms for Euclidean Max-Cut. - Nicolas Menand; Erik Waingarten (CoRR, 2025)

Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures. - Jie Gao; Rajesh Jayaram; Benedikt Kolbe; Shay Sapir; Chris Schwiegelshohn; Sandeep Silwal; Erik Waingarten (CoRR, 2025)

Sparse Navigable Graphs for Nearest Neighbor Search: Algorithms and Hardness. - Sanjeev Khanna; Ashwin Padaki; Erik Waingarten (CoRR, 2025)

Instance-Optimal Uniformity Testing and Tracking. - Guy Blanc; Clément L. Canonne; Erik Waingarten (CoRR, 2025)

Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair. - Lorenzo Beretta 001; Vincent Cohen-Addad; Rajesh Jayaram; Erik Waingarten (CoRR, 2025)