| 2026 | STOC | Restriction Trees for Sparsity and Applications. | Arkadev Chattopadhyay, Yogesh Dahiya, Shachar Lovett |
| 2026 | STOC | Locally Computable High Independence Hashing. | Yevgeniy Dodis, Shachar Lovett, Daniel Wichs |
| 2025 | ALT | Do PAC-Learners Learn the Marginal Distribution? | Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan |
| 2025 | FOCS | Quasipolynomial Bounds for the Corners Theorem. | Michael Jaber, Yang P. Liu, Shachar Lovett, Anthony Ostuni, Mehtaab Sawhney |
| 2024 | ICALP | Refuting Approaches to the Log-Rank Conjecture for XOR Functions. | Hamed Hatami, Kaave Hosseini, Shachar Lovett, Anthony Ostuni |
| 2024 | STOC | New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms. | Amir Abboud, Nick Fischer, Zander Kelley, Shachar Lovett, Raghu Meka |
| 2024 | STOC | Explicit Separations between Randomized and Deterministic Number-on-Forehead Communication. | Zander Kelley, Shachar Lovett, Raghu Meka |
| 2023 | COLT | Exponential Hardness of Reinforcement Learning with Linear Function Approximation. | Sihan Liu, Gaurav Mahajan, Daniel Kane, Shachar Lovett, Gellrt Weisz, Csaba Szepesvri |
| 2023 | FOCS | Streaming Lower Bounds and Asymmetric Set-Disjointness. | Shachar Lovett, Jiapeng Zhang |
| 2023 | SODA | Sampling Equilibria: Fast No-Regret Learning in Structured Games. | Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu, Shachar Lovett |
| 2022 | COLT | Realizable Learning is All You Need. | Max Hopkins, Daniel M. Kane, Shachar Lovett, Gaurav Mahajan |
| 2022 | COLT | Computational-Statistical Gap in Reinforcement Learning. | Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan |
| 2022 | SODA | High Dimensional Expanders: Eigenstripping, Pseudorandomness, and Unique Games. | Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett |
| 2022 | STOC | Hypercontractivity on high dimensional expanders. | Mitali Bafna, Max Hopkins, Tali Kaufman, Shachar Lovett |
| 2021 | COLT | Bounded Memory Active Learning through Enriched Queries. | Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz |
| 2021 | ICML | Bilinear Classes: A Structural Framework for Provable Generalization in RL. | Simon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang |
| 2021 | STOC | Log-rank and lifting for AND-functions. | Alexander Knop, Shachar Lovett, Sam McGuire, Weiqiang Yuan |
| 2020 | COLT | Noise-tolerant, Reliable Active Classification with Comparison Queries. | Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan |
| 2020 | FOCS | Point Location and Active Learning: Learning Halfspaces Almost Optimally. | Max Hopkins, Daniel Kane, Shachar Lovett, Gaurav Mahajan |
| 2020 | STOC | Improved bounds for the sunflower lemma. | Ryan Alweiss, Shachar Lovett, Kewen Wu, Jiapeng Zhang |
| 2020 | STOC | XOR lemmas for resilient functions against polynomials. | Eshan Chattopadhyay, Pooya Hatami, Kaave Hosseini, Shachar Lovett, David Zuckerman |
| 2020 | STOC | Decision list compression by mild random restrictions. | Shachar Lovett, Kewen Wu, Jiapeng Zhang |
| 2019 | STOC | DNF sparsification beyond sunflowers. | Shachar Lovett, Jiapeng Zhang |
| 2018 | FOCS | MDS Matrices over Small Fields: A Proof of the GM-MDS Conjecture. | Shachar Lovett |
| 2018 | ICALP | Generalized Comparison Trees for Point-Location Problems. | Daniel M. Kane, Shachar Lovett, Shay Moran |
| 2018 | SODA | Probabilistic Existence of Large Sets of Designs. | Shachar Lovett, Sankeerth Rao, Alexander Vardy |
| 2018 | SODA | The Robust Sensitivity of Boolean Functions. | Shachar Lovett, Avishay Tal, Jiapeng Zhang |
| 2018 | STOC | The gram-schmidt walk: a cure for the Banaszczyk blues. | Nikhil Bansal, Daniel Dadush, Shashwat Garg, Shachar Lovett |
| 2018 | STOC | Near-optimal linear decision trees for k-SUM and related problems. | Daniel M. Kane, Shachar Lovett, Shay Moran |
| 2017 | COLT | Noisy Population Recovery from Unknown Noise. | Shachar Lovett, Jiapeng Zhang |
| 2017 | FOCS | Active Classification with Comparison Queries. | Daniel M. Kane, Shachar Lovett, Shay Moran, Jiapeng Zhang |
| 2017 | FOCS | The Independence Number of the Birkhoff Polytope Graph, and Applications to Maximally Recoverable Codes. | Daniel Kane, Shachar Lovett, Sankeerth Rao |
| 2017 | TCC | On the Impossibility of Entropy Reversal, and Its Application to Zero-Knowledge Proofs. | Shachar Lovett, Jiapeng Zhang |
| 2016 | FOCS | Structure of Protocols for XOR Functions. | Hamed Hatami, Kaave Hosseini, Shachar Lovett |
| 2016 | ISIT | Affine-malleable extractors, spectrum doubling, and application to privacy amplification. | Divesh Aggarwal, Kaave Hosseini, Shachar Lovett |
| 2016 | STOC | Algebraic attacks against random local functions and their countermeasures. | Benny Applebaum, Shachar Lovett |
| 2015 | STOC | The List Decoding Radius of Reed-Muller Codes over Small Fields. | Abhishek Bhowmick, Shachar Lovett |
| 2015 | STOC | Rectangles Are Nonnegative Juntas. | Mika Gs, Shachar Lovett, Raghu Meka, Thomas Watson, David Zuckerman |
| 2015 | STOC | Improved Noisy Population Recovery, and Reverse Bonami-Beckner Inequality for Sparse Functions. | Shachar Lovett, Jiapeng Zhang |
| 2014 | ICALP | En Route to the Log-Rank Conjecture: New Reductions and Equivalent Formulations. | Dmitry Gavinsky, Shachar Lovett |
| 2014 | STOC | Non-malleable codes from additive combinatorics. | Divesh Aggarwal, Yevgeniy Dodis, Shachar Lovett |
| 2014 | STOC | Communication is bounded by root of rank. | Shachar Lovett |
| 2013 | FOCS | Estimating the Distance from Testable Affine-Invariant Properties. | Hamed Hatami, Shachar Lovett |
| 2013 | SODA | Testing Low Complexity Affine-Invariant Properties. | Arnab Bhattacharyya, Eldar Fischer, Shachar Lovett |
| 2013 | STOC | Every locally characterized affine-invariant property is testable. | Arnab Bhattacharyya, Eldar Fischer, Hamed Hatami, Pooya Hatami, Shachar Lovett |
| 2013 | STOC | New bounds for matching vector families. | Abhishek Bhowmick, Zeev Dvir, Shachar Lovett |
| 2012 | COLT | Unsupervised SVMs: On the Complexity of the Furthest Hyperplane Problem. | Zohar Shay Karnin, Edo Liberty, Shachar Lovett, Roy Schwartz, Omri Weinstein |
| 2012 | FOCS | Large Deviation Bounds for Decision Trees and Sampling Lower Bounds for AC0-Circuits. | Chris Beck, Russell Impagliazzo, Shachar Lovett |
| 2012 | FOCS | An Additive Combinatorics Approach Relating Rank to Communication Complexity. | Eli Ben-Sasson, Shachar Lovett, Noga Ron-Zewi |
| 2012 | FOCS | Constructive Discrepancy Minimization by Walking on the Edges. | Shachar Lovett, Raghu Meka |
| 2012 | STOC | Subspace evasive sets. | Zeev Dvir, Shachar Lovett |
| 2012 | STOC | Probabilistic existence of rigid combinatorial structures. | Greg Kuperberg, Shachar Lovett, Ron Peled |
| 2011 | FOCS | New Extension of the Weil Bound for Character Sums with Applications to Coding. | Tali Kaufman, Shachar Lovett |
| 2011 | STOC | Correlation testing for affine invariant properties on F | Hamed Hatami, Shachar Lovett |
| 2010 | FOCS | Pseudorandom Generators for CC0[p] and the Fourier Spectrum of Low-Degree Polynomials over Finite Fields. | Shachar Lovett, Partha Mukhopadhyay, Amir Shpilka |
| 2010 | FOCS | A Lower Bound for Dynamic Approximate Membership Data Structures. | Shachar Lovett, Ely Porat |
| 2009 | STOC | On cryptography with auxiliary input. | Yevgeniy Dodis, Yael Tauman Kalai, Shachar Lovett |
| 2008 | FOCS | Worst Case to Average Case Reductions for Polynomials. | Tali Kaufman, Shachar Lovett |
| 2008 | STOC | Unconditional pseudorandom generators for low degree polynomials. | Shachar Lovett |
| 2008 | STOC | Inverse conjecture for the gowers norm is false. | Shachar Lovett, Roy Meshulam, Alex Samorodnitsky |
| 2008 | STACS | Lower bounds for adaptive linearity tests. | Shachar Lovett |