Amid, Ehsan

25 publications

ALT 2025 How Rotation Invariant Algorithms Are Fooled by Noise on Sparse Targets Manfred K. Warmuth, Wojciech Kot\polishlowski, Matt Jones, Ehsan Amid

ICLR 2025 Restructuring Vector Quantization with the Rotation Trick Christopher Fifty, Ronald Guenther Junkins, Dennis Duan, Aniketh Iyengar, Jerry Weihong Liu, Ehsan Amid, Sebastian Thrun, Christopher Re

ICLR 2024 Context-Aware Meta-Learning Christopher Fifty, Dennis Duan, Ronald Guenther Junkins, Ehsan Amid, Jure Leskovec, Christopher Re, Sebastian Thrun

NeurIPS 2024 Hyperbolic Embeddings of Supervised Models Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen, Manfred K. Warmuth

AAAI 2024 Optimal Transport with Tempered Exponential Measures Ehsan Amid, Frank Nielsen, Richard Nock, Manfred K. Warmuth

NeurIPS 2023 Boosting with Tempered Exponential Measures Richard Nock, Ehsan Amid, Manfred Warmuth

AISTATS 2023 Clustering Above Exponential Families with Tempered Exponential Measures Ehsan Amid, Richard Nock, Manfred K. Warmuth

NeurIPSW 2023 Context-Aware Meta-Learning Christopher Fifty, Dennis Duan, Ronald Guenther Junkins, Ehsan Amid, Jure Leskovec, Christopher Re, Sebastian Thrun

ICLR 2023 Distributionally Robust Post-Hoc Classifiers Under Prior Shifts Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar

TMLR 2023 Layerwise Bregman Representation Learning of Neural Networks with Applications to Knowledge Distillation Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K Warmuth

COLT 2023 Open Problem: Learning Sparse Linear Concepts by Priming the Features Manfred K. Warmuth, Ehsan Amid

AISTATS 2022 LocoProp: Enhancing BackProp via Local Loss Optimization Ehsan Amid, Rohan Anil, Manfred Warmuth

NeurIPSW 2022 Fast Implicit Constrained Optimization of Non-Decomposable Objectives for Deep Networks Yatong Chen, Abhishek Kumar, Yang Liu, Ehsan Amid

NeurIPSW 2022 Fishy: Layerwise Fisher Approximation for Higher-Order Neural Network Optimization Abel Peirson, Ehsan Amid, Yatong Chen, Vladimir Feinberg, Manfred K Warmuth, Rohan Anil

ICML 2022 Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Thomas Steinke, Vinith M Suriyakumar, Om Thakkar, Abhradeep Thakurta

ALT 2021 A Case Where a Spindly Two-Layer Linear Network Decisively Outperforms Any Neural Network with a Fully Connected Input Layer Manfred K. Warmuth, Wojciech Kotłowski, Ehsan Amid

NeurIPS 2021 Efficiently Identifying Task Groupings for Multi-Task Learning Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn

AAAI 2020 An Implicit Form of Krasulina's K-PCA Update Without the Orthonormality Constraint Ehsan Amid, Manfred K. Warmuth

UAI 2020 Divergence-Based Motivation for Online EM and Combining Hidden Variable Models Ehsan Amid, Manfred K. Warmuth

NeurIPS 2020 Reparameterizing Mirror Descent as Gradient Descent Ehsan Amid, Manfred K. Warmuth

COLT 2020 Winnowing with Gradient Descent Ehsan Amid, Manfred K. Warmuth

NeurIPS 2019 Robust Bi-Tempered Logistic Loss Based on Bregman Divergences Ehsan Amid, Manfred K. Warmuth, Rohan Anil, Tomer Koren

AISTATS 2019 Two-Temperature Logistic Regression Based on the Tsallis Divergence Ehsan Amid, Manfred K. Warmuth, Sriram Srinivasan

ECML-PKDD 2015 A Kernel-Learning Approach to Semi-Supervised Clustering with Relative Distance Comparisons Ehsan Amid, Aristides Gionis, Antti Ukkonen

ICML 2015 Multiview Triplet Embedding: Learning Attributes in Multiple Maps Ehsan Amid, Antti Ukkonen