Volume Regularization for Binary Classification. - Koby Crammer; Tal Wagner (NIPS, 2012)

Cheeger-type approximation for sparsest $st$-cut. - Robert Krauthgamer; Tal Wagner (CoRR, 2014)

Towards Resistance Sparsifiers. - Michael Dinitz; Robert Krauthgamer; Tal Wagner (APPROX-RANDOM, 2015)

A sampling-based approach to accelerating queries in log management systems. - Tal Wagner; Eric Schkufza; Udi Wieder (SPLASH (Companion Volume), 2016)

A Graph-Theoretic Approach to Multitasking. - Jonathan D. Cohen 003; Biswadip Dey; Tom Griffiths 001; Sebastian Musslick; Kayhan Özcimder; Daniel Reichman 001; Igor Shinkar; Tal Wagner (CoRR, 2016)

Cheeger-Type Approximation for Sparsest st-Cut. - Robert Krauthgamer; Tal Wagner (ACM Trans. Algorithms, 2016)

A graph-theoretic approach to multitasking. - Noga Alon; Daniel Reichman 001; Igor Shinkar; Tal Wagner; Sebastian Musslick; Jonathan D. Cohen 003; Tom Griffiths 001; Biswadip Dey; Kayhan Özcimder (NIPS, 2017)

Practical Data-Dependent Metric Compression with Provable Guarantees. - Piotr Indyk; Ilya P. Razenshteyn; Tal Wagner (NIPS, 2017)

Near-Optimal (Euclidean) Metric Compression. - Piotr Indyk; Tal Wagner (SODA, 2017)

Approximate Nearest Neighbors in Limited Space. - Piotr Indyk; Tal Wagner (COLT, 2018)

Semi-Supervised Learning on Data Streams via Temporal Label Propagation. - Tal Wagner; Sudipto Guha; Shiva Prasad Kasiviswanathan; Nina Mishra (ICML, 2018)

Sample-Optimal Low-Rank Approximation of Distance Matrices. - Piotr Indyk; Ali Vakilian; Tal Wagner; David P. Woodruff (COLT, 2019)

Scalable Fair Clustering. - Arturs Backurs; Piotr Indyk; Krzysztof Onak; Baruch Schieber; Ali Vakilian; Tal Wagner (ICML, 2019)

Space and Time Efficient Kernel Density Estimation in High Dimensions. - Arturs Backurs; Piotr Indyk; Tal Wagner (NeurIPS, 2019)

Eccentricities via Parallel Set Cover (Brief Announcement). - Tal Wagner (SPAA, 2019)

Learning Sublinear-Time Indexing for Nearest Neighbor Search. - Yihe Dong; Piotr Indyk; Ilya P. Razenshteyn; Tal Wagner (CoRR, 2019)

Scalable Nearest Neighbor Search for Optimal Transport. - Yihe Dong; Piotr Indyk; Ilya P. Razenshteyn; Tal Wagner (CoRR, 2019)

Eccentricity Heuristics through Sublinear Analysis Lenses. - Tal Wagner (APOCS, 2020)

Scalable Nearest Neighbor Search for Optimal Transport. - Arturs Backurs; Yihe Dong; Piotr Indyk; Ilya P. Razenshteyn; Tal Wagner (ICML, 2020)

Multitasking Capacity: Hardness Results and Improved Constructions. - Noga Alon; Jonathan D. Cohen 003; Thomas L. Griffiths 001; Pasin Manurangsi; Daniel Reichman 001; Igor Shinkar; Tal Wagner; Alexander Y. Ku (SIAM J. Discret. Math., 2020)

Learning-based Support Estimation in Sublinear Time. - Talya Eden; Piotr Indyk; Shyam Narayanan; Ronitt Rubinfeld; Sandeep Silwal; Tal Wagner (ICLR, 2021)

Faster Kernel Matrix Algebra via Density Estimation. - Arturs Backurs; Piotr Indyk; Cameron Musco; Tal Wagner (ICML, 2021)

Few-Shot Data-Driven Algorithms for Low Rank Approximation. - Piotr Indyk; Tal Wagner; David P. Woodruff (NeurIPS, 2021)

Generalization Bounds for Data-Driven Numerical Linear Algebra. - Peter L. Bartlett; Piotr Indyk; Tal Wagner (COLT, 2022)

Triangle and Four Cycle Counting with Predictions in Graph Streams. - Justin Y. Chen; Talya Eden; Piotr Indyk; Honghao Lin; Shyam Narayanan; Ronitt Rubinfeld; Sandeep Silwal; Tal Wagner; David P. Woodruff; Michael Zhang (ICLR, 2022)

Streaming Algorithms for Support-Aware Histograms. - Justin Y. Chen; Piotr Indyk; Tal Wagner (ICML, 2022)

Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. - Anders Aamand; Justin Y. Chen; Piotr Indyk; Shyam Narayanan; Ronitt Rubinfeld; Nicholas Schiefer; Sandeep Silwal; Tal Wagner (NeurIPS, 2022)

Unveiling Transformers with LEGO: a synthetic reasoning task. - Yi Zhang; Arturs Backurs; Sébastien Bubeck; Ronen Eldan; Suriya Gunasekar; Tal Wagner (CoRR, 2022)

Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport. - David Alvarez-Melis; Nicolò Fusi; Lester Mackey; Tal Wagner (CoRR, 2022)

Optimal (Euclidean) Metric Compression. - Piotr Indyk; Tal Wagner (SIAM J. Comput., 2022)

Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees. - Nicholas Schiefer; Justin Y. Chen; Piotr Indyk; Shyam Narayanan; Sandeep Silwal; Tal Wagner (ACDA, 2023)

Fast Private Kernel Density Estimation via Locality Sensitive Quantization. - Tal Wagner; Yonatan Naamad; Nina Mishra (ICML, 2023)

Learning Space Partitions for Nearest Neighbor Search. - Yihe Dong; Piotr Indyk; Ilya P. Razenshteyn; Tal Wagner (IEEE Data Eng. Bull., 2023)

Erratum: Multitasking Capacity: Hardness Results and Improved Constructions. - Noga Alon; Jonathan D. Cohen 003; Thomas L. Griffiths 001; Pasin Manurangsi; Daniel Reichman 001; Igor Shinkar; Tal Wagner (SIAM J. Discret. Math., 2024)

Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions. - Piotr Indyk; Michael Kapralov; Kshiteej Sheth; Tal Wagner (ICLR, 2025)

Learning from End User Data with Shuffled Differential Privacy over Kernel Densities. - Tal Wagner (ICLR, 2025)

Private Text Generation by Seeding Large Language Model Prompts. - Supriya Nagesh; Justin Y. Chen; Nina Mishra; Tal Wagner (CoRR, 2025)