| 2026 | COLT | Clipping the Price of Adaptivity at the Tail. | Itai Kreisler, Yair Carmon, Oliver Hinder |
| 2024 | COLT | The Price of Adaptivity in Stochastic Convex Optimization. | Yair Carmon, Oliver Hinder |
| 2024 | COLT | Accelerated Parameter-Free Stochastic Optimization. | Itai Kreisler, Maor Ivgi, Oliver Hinder, Yair Carmon |
| 2024 | SODA | A Whole New Ball Game: A Primal Accelerated Method for Matrix Games and Minimizing the Maximum of Smooth Functions. | Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2023 | FOCS | ReSQueing Parallel and Private Stochastic Convex Optimization. | Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Daogao Liu, Aaron Sidford, Kevin Tian |
| 2023 | ICLR | Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds. | Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon |
| 2023 | ICML | DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule. | Maor Ivgi, Oliver Hinder, Yair Carmon |
| 2023 | ICML | Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond. | Itai Kreisler, Mor Shpigel Nacson, Daniel Soudry, Yair Carmon |
| 2022 | COLT | Making SGD Parameter-Free. | Yair Carmon, Oliver Hinder |
| 2022 | EMNLP | Scaling Laws Under the Microscope: Predicting Transformer Performance from Small Scale Experiments. | Maor Ivgi, Yair Carmon, Jonathan Berant |
| 2022 | ICML | RECAPP: Crafting a More Efficient Catalyst for Convex Optimization. | Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2022 | ICML | Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. | Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt |
| 2021 | COLT | Thinking Inside the Ball: Near-Optimal Minimization of the Maximal Loss. | Yair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2021 | ICML | Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. | John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt |
| 2020 | COLT | Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations. | Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan |
| 2020 | FOCS | Coordinate Methods for Matrix Games. | Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian |
| 2019 | COLT | A Rank-1 Sketch for Matrix Multiplicative Weights. | Yair Carmon, John C. Duchi, Aaron Sidford, Kevin Tian |
| 2017 | ICML | "Convex Until Proven Guilty": Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions. | Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford |
| 2013 | ISIT | The role of lookahead in estimation under Gaussian noise. | Kartik Venkat, Tsachy Weissman, Yair Carmon, Shlomo Shamai |