| 2026 | EACL | We Are What We Repeatedly Do: Improving Long Context Instruction Following. | Preston K. Robinette, Andrew Hard, Swaroop Ramaswamy, Ehsan Amid, Rajiv Mathews, Taylor T. Johnson |
| 2025 | ALT | How rotation invariant algorithms are fooled by noise on sparse targets. | Manfred K. Warmuth, Wojciech Kotlowski, Matt Jones, Ehsan Amid |
| 2025 | ICLR | Restructuring Vector Quantization with the Rotation Trick. | Christopher Fifty, Ronald Guenther Junkins, Dennis Duan, Aniketh Iyengar, Jerry Weihong Liu, Ehsan Amid, Sebastian Thrun, Christopher R |
| 2024 | AAAI | Optimal Transport with Tempered Exponential Measures. | Ehsan Amid, Frank Nielsen, Richard Nock, Manfred K. Warmuth |
| 2024 | ICLR | Context-Aware Meta-Learning. | Christopher Fifty, Dennis Duan, Ronald G. Junkins, Ehsan Amid, Jure Leskovec, Christopher R, Sebastian Thrun |
| 2023 | AISTATS | Clustering above Exponential Families with Tempered Exponential Measures. | Ehsan Amid, Richard Nock, Manfred K. Warmuth |
| 2023 | COLT | Open Problem: Learning sparse linear concepts by priming the features. | Manfred K. Warmuth, Ehsan Amid |
| 2023 | ICLR | Distributionally Robust Post-hoc Classifiers under Prior Shifts. | Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar |
| 2023 | KDD | To Aggregate or Not? Learning with Separate Noisy Labels. | Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu |
| 2022 | AISTATS | LocoProp: Enhancing BackProp via Local Loss Optimization. | Ehsan Amid, Rohan Anil, Manfred K. Warmuth |
| 2022 | ICML | Public Data-Assisted Mirror Descent for Private Model Training. | Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta |
| 2022 | Interspeech | Extracting Targeted Training Data from ASR Models, and How to Mitigate It. | Ehsan Amid, Om Dipakbhai Thakkar, Arun Narayanan, Rajiv Mathews, Franoise Beaufays |
| 2021 | ALT | A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer. | Manfred K. Warmuth, Wojciech Kotlowski, Ehsan Amid |
| 2020 | AAAI | An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint. | Ehsan Amid, Manfred K. Warmuth |
| 2020 | COLT | Winnowing with Gradient Descent. | Ehsan Amid, Manfred K. Warmuth |
| 2020 | ICIP | Rank-Smoothed Pairwise Learning In Perceptual Quality Assessment. | Hossein Talebi, Ehsan Amid, Peyman Milanfar, Manfred K. Warmuth |
| 2020 | UAI | Divergence-Based Motivation for Online EM and Combining Hidden Variable Models. | Ehsan Amid, Manfred K. Warmuth |
| 2019 | AISTATS | Two-temperature logistic regression based on the Tsallis divergence. | Ehsan Amid, Manfred K. Warmuth, Sriram Srinivasan |
| 2015 | ICML | Multiview Triplet Embedding: Learning Attributes in Multiple Maps. | Ehsan Amid, Antti Ukkonen |
| 2014 | ICASSP | Unsupervised feature extraction for multimedia event detection and ranking using audio content. | Ehsan Amid, Annamaria Mesaros, Kalle J. Palomki, Jorma Laaksonen, Mikko Kurimo |