← Authors

Ehsan Amid

22 papers · 2015–2026 · 10 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (10) πŸ—ΊοΈ Taxonomy Completionist (39) 🀝 Dynamic Duo (12) πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ’Ž Century Club (21) πŸ—ƒοΈ Keyword Collector (82) πŸ”₯ Unstoppable (7)

Conferences

NIPS (5) AISTATS (3) ICLR (3) AAAI (2) ALT (2) COLT (2) ICML (2) EACL (1) INTERSPEECH (1) UAI (1)

Top co-authors

Manfred K. Warmuth (12) Richard Nock (4) Rajiv Mathews (3) Rohan Anil (3) Sebastian Thrun (2) Christopher Re (2) Ronald Guenther Junkins (2) Christopher Fifty (2) Swaroop Ramaswamy (2) Manfred Warmuth (2)

Keywords

gradient descent (4) bregman divergence (3) tempered exponential measure (3) online learning (3) expectation maximization (2) metric learning (2) multiplicative update (2) temperature parameter (2) sparse target (2) mirror descent (2) k-means clustering (1) logistic regression (1) matrix factorization (1) embedding learning (1) neural network training (1) stochastic gradient descent (1) computer vision (1) instruction following (1) principal component analysis (1) multi-task learning (1)

Papers

We Are What We Repeatedly Do: Improving Long Context Instruction Following EACL 2026
How rotation invariant algorithms are fooled by noise on sparse targets ALT 2025
Restructuring Vector Quantization with the Rotation Trick ICLR 2025
Context-Aware Meta-Learning ICLR 2024
Hyperbolic Embeddings of Supervised Models NIPS 2024
Optimal Transport with Tempered Exponential Measures AAAI 2024
Clustering above Exponential Families with Tempered Exponential Measures AISTATS 2023
Open Problem: Learning sparse linear concepts by priming the features COLT 2023
Distributionally Robust Post-hoc Classifiers under Prior Shifts ICLR 2023
Boosting with Tempered Exponential Measures NIPS 2023
LocoProp: Enhancing BackProp via Local Loss Optimization AISTATS 2022
Public Data-Assisted Mirror Descent for Private Model Training ICML 2022
Extracting Targeted Training Data from ASR Models, and How to Mitigate It INTERSPEECH 2022
Efficiently Identifying Task Groupings for Multi-Task Learning NIPS 2021
A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer ALT 2021
Reparameterizing Mirror Descent as Gradient Descent NIPS 2020
Divergence-Based Motivation for Online EM and Combining Hidden Variable Models UAI 2020
An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint AAAI 2020
Winnowing with Gradient Descent COLT 2020
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences NIPS 2019
Two-temperature logistic regression based on the Tsallis divergence AISTATS 2019
Multiview Triplet Embedding: Learning Attributes in Multiple Maps ICML 2015