Ehsan Amid - RankMe

70 papers A* 15A 5B 3Misc 1Journal 39Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	We Are What We Repeatedly Do: Improving Long Context Instruction Following. EACL (Findings) Preston K. Robinette, Andrew Hard, Swaroop Ramaswamy, Ehsan Amid, Rajiv Mathews, Taylor T. Johnson
2025	B	`conf`	How rotation invariant algorithms are fooled by noise on sparse targets. ALT Manfred K. Warmuth, Wojciech Kotlowski, Matt Jones, Ehsan Amid
2025	J	`jnl`	Principled Foundations for Preference Optimization. CoRR Wenxuan Zhou, Shujian Zhang, Brice Magdalou, John Lambert, Ehsan Amid, Richard Nock, Andrew Hard
2025	A*	`conf`	Restructuring Vector Quantization with the Rotation Trick. ICLR Christopher Fifty, Ronald Guenther Junkins, Dennis Duan, Aniketh Iyengar, Jerry Weihong Liu, Ehsan Amid, Sebastian Thrun, Christopher Ré
2024	A*	`conf`	Context-Aware Meta-Learning. ICLR Christopher Fifty, Dennis Duan, Ronald G. Junkins, Ehsan Amid, Jure Leskovec, Christopher Ré, Sebastian Thrun
2024	A*	`conf`	Hyperbolic Embeddings of Supervised Models. NeurIPS Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen, Manfred K. Warmuth
2024	J	`jnl`	Learning from straggler clients in federated learning. CoRR Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil
2024	J	`jnl`	Noise misleads rotation invariant algorithms on sparse targets. CoRR Manfred K. Warmuth, Wojciech Kotlowski, Matt Jones, Ehsan Amid
2024	A*	`conf`	Optimal Transport with Tempered Exponential Measures. AAAI Ehsan Amid, Frank Nielsen, Richard Nock, Manfred K. Warmuth
2024	J	`jnl`	Restructuring Vector Quantization with the Rotation Trick. CoRR Christopher Fifty, Ronald G. Junkins, Dennis Duan, Aniketh Iger, Jerry W. Liu, Ehsan Amid, Sebastian Thrun, Christopher Ré
2024	J	`jnl`	Tempered Calculus for ML: Application to Hyperbolic Model Embedding. CoRR Richard Nock, Ehsan Amid, Frank Nielsen, Alexander Soen, Manfred K. Warmuth
2023	J	`jnl`	Benchmarking Neural Network Training Algorithms. CoRR George E. Dahl, Frank Schneider, Zachary Nado, Naman Agarwal, Chandramouli Shama Sastry, Philipp Hennig, Sourabh Medapati, Runa Eschenhagen, Priya Kasimbeg, Daniel Suo, Juhan Bae, Justin Gilmer, Abel L. Peirson, Bilal Khan, Rohan Anil, Mike Rabbat, Shankar Krishnan, Daniel Snider, Ehsan Amid, Kongtao Chen, Chris J. Maddison, Rakshith Vasudev, Michal Badura, Ankush Garg, Peter Mattson
2023	A*	`conf`	Boosting with Tempered Exponential Measures. NeurIPS Richard Nock, Ehsan Amid, Manfred K. Warmuth
2023	J	`jnl`	Boosting with Tempered Exponential Measures. CoRR Richard Nock, Ehsan Amid, Manfred K. Warmuth
2023	A	`conf`	Clustering above Exponential Families with Tempered Exponential Measures. AISTATS Ehsan Amid, Richard Nock, Manfred K. Warmuth
2023	J	`jnl`	Context-Aware Meta-Learning. CoRR Christopher Fifty, Dennis Duan, Ronald G. Junkins, Ehsan Amid, Jure Leskovec, Christopher Ré, Sebastian Thrun
2023	A*	`conf`	Distributionally Robust Post-hoc Classifiers under Prior Shifts. ICLR Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
2023	J	`jnl`	Distributionally Robust Post-hoc Classifiers under Prior Shifts. CoRR Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
2023	J	`jnl`	Harnessing Simulation for Molecular Embeddings. CoRR Christopher Fifty, Joseph M. Paggi, Ehsan Amid, Jure Leskovec, Ron O. Dror
2023	J	`jnl`	Heterogeneous Federated Learning Using Knowledge Codistillation. CoRR Jared Lichtarge, Ehsan Amid, Shankar Kumar, Tien-Ju Yang, Rohan Anil, Rajiv Mathews
2023	J	`jnl`	Layerwise Bregman Representation Learning of Neural Networks with Applications to Knowledge Distillation. Trans. Mach. Learn. Res. Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K. Warmuth
2023	A*	`conf`	Open Problem: Learning sparse linear concepts by priming the features. COLT Manfred K. Warmuth, Ehsan Amid
2023	J	`jnl`	Optimal Transport with Tempered Exponential Measures. CoRR Ehsan Amid, Frank Nielsen, Richard Nock, Manfred K. Warmuth
2023	J	`jnl`	The Tempered Hilbert Simplex Distance and Its Application To Non-linear Embeddings of TEMs. CoRR Ehsan Amid, Frank Nielsen, Richard Nock, Manfred K. Warmuth
2023	—	`conf`	To Aggregate or Not? Learning with Separate Noisy Labels. CSW@WSDM Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
2023	A*	`conf`	To Aggregate or Not? Learning with Separate Noisy Labels. KDD Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
2022	J	`jnl`	Clustering above Exponential Families with Tempered Exponential Measures. CoRR Ehsan Amid, Richard Nock, Manfred K. Warmuth
2022	A	`conf`	Extracting Targeted Training Data from ASR Models, and How to Mitigate It. INTERSPEECH Ehsan Amid, Om Dipakbhai Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays
2022	J	`jnl`	Extracting Targeted Training Data from ASR Models, and How to Mitigate It. CoRR Ehsan Amid, Om Thakkar, Arun Narayanan, Rajiv Mathews, Françoise Beaufays
2022	J	`jnl`	Layerwise Bregman Representation Learning with Applications to Knowledge Distillation. CoRR Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K. Warmuth
2022	J	`jnl`	Learning from Randomly Initialized Neural Network Features. CoRR Ehsan Amid, Rohan Anil, Wojciech Kotlowski, Manfred K. Warmuth
2022	A	`conf`	LocoProp: Enhancing BackProp via Local Loss Optimization. AISTATS Ehsan Amid, Rohan Anil, Manfred K. Warmuth
2022	A*	`conf`	Public Data-Assisted Mirror Descent for Private Model Training. ICML Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2022	J	`jnl`	Step-size Adaptation Using Exponentiated Gradient Updates. CoRR Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K. Warmuth
2022	J	`jnl`	To Aggregate or Not? Learning with Separate Noisy Labels. CoRR Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu
2021	B	`conf`	A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer. ALT Manfred K. Warmuth, Wojciech Kotlowski, Ehsan Amid
2021	J	`jnl`	Constrained Instance and Class Reweighting for Robust Learning under Label Noise. CoRR Abhishek Kumar, Ehsan Amid
2021	A*	`conf`	Efficiently Identifying Task Groupings for Multi-Task Learning. NeurIPS Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
2021	J	`jnl`	Efficiently Identifying Task Groupings for Multi-Task Learning. CoRR Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
2021	J	`jnl`	Exponentiated Gradient Reweighting for Robust Training Under Label Noise and Beyond. CoRR Negin Majidi, Ehsan Amid, Hossein Talebi, Manfred K. Warmuth
2021	J	`jnl`	LocoProp: Enhancing BackProp via Local Loss Optimization. CoRR Ehsan Amid, Rohan Anil, Manfred K. Warmuth
2021	—	`conf`	Privacy-Preserving Wireless Federated Learning Exploiting Inherent Hardware Impairments. CAMAD Sina Rezaei Aghdam, Ehsan Amid, Marija Furdek, Alexandre Graell i Amat
2021	J	`jnl`	Privacy-Preserving Wireless Federated Learning Exploiting Inherent Hardware Impairments. CoRR Sina Rezaei Aghdam, Ehsan Amid, Marija Furdek, Alexandre Graell i Amat
2021	J	`jnl`	Public Data-Assisted Mirror Descent for Private Model Training. CoRR Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta
2020	J	`jnl`	A case where a spindly two-layer linear network whips any neural network with a fully connected input layer. CoRR Manfred K. Warmuth, Wojciech Kotlowski, Ehsan Amid
2020	A*	`conf`	An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint. AAAI Ehsan Amid, Manfred K. Warmuth
2020	A	`conf`	Divergence-Based Motivation for Online EM and Combining Hidden Variable Models. UAI Ehsan Amid, Manfred K. Warmuth
2020	J	`jnl`	Interpolating Between Gradient Descent and Exponentiated Gradient Using Reparameterized Gradient Descent. CoRR Ehsan Amid, Manfred K. Warmuth
2020	J	`jnl`	Measuring and Harnessing Transference in Multi-Task Learning. CoRR Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
2020	B	`conf`	Rank-Smoothed Pairwise Learning In Perceptual Quality Assessment. ICIP Hossein Talebi, Ehsan Amid, Peyman Milanfar, Manfred K. Warmuth
2020	J	`jnl`	Rank-smoothed Pairwise Learning In Perceptual Quality Assessment. CoRR Hossein Talebi, Ehsan Amid, Peyman Milanfar, Manfred K. Warmuth
2020	A*	`conf`	Reparameterizing Mirror Descent as Gradient Descent. NeurIPS Ehsan Amid, Manfred K. Warmuth
2020	—	`—`	Tempered Bregman Divergence for Continuous and Discrete Time Mirror Descent and Robust Classification. Ehsan Amid
2020	A*	`conf`	Winnowing with Gradient Descent. COLT Ehsan Amid, Manfred K. Warmuth
2019	J	`jnl`	An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint. CoRR Ehsan Amid, Manfred K. Warmuth
2019	J	`jnl`	Divergence-Based Motivation for Online EM and Combining Hidden Variable Models. CoRR Ehsan Amid, Manfred K. Warmuth
2019	A*	`conf`	Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. NeurIPS Ehsan Amid, Manfred K. Warmuth, Rohan Anil, Tomer Koren
2019	J	`jnl`	Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. CoRR Ehsan Amid, Manfred K. Warmuth, Rohan Anil, Tomer Koren
2019	J	`jnl`	TriMap: Large-scale Dimensionality Reduction Using Triplets. CoRR Ehsan Amid, Manfred K. Warmuth
2019	A	`conf`	Two-temperature logistic regression based on the Tsallis divergence. AISTATS Ehsan Amid, Manfred K. Warmuth, Sriram Srinivasan
2018	J	`jnl`	A more globally accurate dimensionality reduction method using triplets. CoRR Ehsan Amid, Manfred K. Warmuth
2017	J	`jnl`	Two-temperature logistic regression based on the Tsallis divergence. CoRR Ehsan Amid, Manfred K. Warmuth
2016	J	`jnl`	Semi-supervised Kernel Metric Learning Using Relative Comparisons. CoRR Ehsan Amid, Aristides Gionis, Antti Ukkonen
2016	J	`jnl`	t-Exponential Triplet Embedding. CoRR Ehsan Amid, Nikos Vlassis, Manfred K. Warmuth
2015	—	`conf`	A Kernel-Learning Approach to Semi-supervised Clustering with Relative Distance Comparisons. ECML/PKDD (1) Ehsan Amid, Aristides Gionis, Antti Ukkonen
2015	A*	`conf`	Multiview Triplet Embedding: Learning Attributes in Multiple Maps. ICML Ehsan Amid, Antti Ukkonen
2015	J	`jnl`	Optimizing the Information Retrieval Trade-off in Data Visualization Using $α$-Divergence. CoRR Ehsan Amid, Onur Dikmen, Erkki Oja
2014	Misc	`conf`	Unsupervised feature extraction for multimedia event detection and ranking using audio content. ICASSP Ehsan Amid, Annamaria Mesaros, Kalle J. Palomäki, Jorma Laaksonen, Mikko Kurimo
2013	—	`conf`	Bayesian Non-parametric Image Segmentation with Markov Random Field Prior. SCIA Ehsan Amid
2013	—	`conf`	PicSOM Experiments in TRECVID 2013. TRECVID Satoru Ishikawa, Markus Koskela, Mats Sjöberg, Jorma Laaksonen, Erkki Oja, Ehsan Amid, Kalle J. Palomäki, Annamaria Mesaros, Mikko Kurimo