Ehsan Amid

Orcid: 0000-0001-6097-0226

Affiliations:
  • Google Brain
  • University of California, Santa Cruz (former)


According to our database1, Ehsan Amid authored at least 49 papers between 2013 and 2024.

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Bibliography

2024
Restructuring Vector Quantization with the Rotation Trick.
CoRR, 2024

Learning from straggler clients in federated learning.
CoRR, 2024

Noise misleads rotation invariant algorithms on sparse targets.
CoRR, 2024

Tempered Calculus for ML: Application to Hyperbolic Model Embedding.
CoRR, 2024

Context-Aware Meta-Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Optimal Transport with Tempered Exponential Measures.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Layerwise Bregman Representation Learning of Neural Networks with Applications to Knowledge Distillation.
Trans. Mach. Learn. Res., 2023

The Tempered Hilbert Simplex Distance and Its Application To Non-linear Embeddings of TEMs.
CoRR, 2023

Heterogeneous Federated Learning Using Knowledge Codistillation.
CoRR, 2023

Benchmarking Neural Network Training Algorithms.
CoRR, 2023

Harnessing Simulation for Molecular Embeddings.
CoRR, 2023

Boosting with Tempered Exponential Measures.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distributionally Robust Post-hoc Classifiers under Prior Shifts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

To Aggregate or Not? Learning with Separate Noisy Labels.
Proceedings of the 4th Crowd Science Workshop on Collaboration of Humans and Learning Algorithms for Data Labeling co-located with ACM International WSDM Conference (WSDM 2023), 2023

Open Problem: Learning sparse linear concepts by priming the features.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Clustering above Exponential Families with Tempered Exponential Measures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Layerwise Bregman Representation Learning with Applications to Knowledge Distillation.
CoRR, 2022

Learning from Randomly Initialized Neural Network Features.
CoRR, 2022

Step-size Adaptation Using Exponentiated Gradient Updates.
CoRR, 2022

Extracting Targeted Training Data from ASR Models, and How to Mitigate It.
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Public Data-Assisted Mirror Descent for Private Model Training.
Proceedings of the International Conference on Machine Learning, 2022

LocoProp: Enhancing BackProp via Local Loss Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Constrained Instance and Class Reweighting for Robust Learning under Label Noise.
CoRR, 2021

Exponentiated Gradient Reweighting for Robust Training Under Label Noise and Beyond.
CoRR, 2021

Efficiently Identifying Task Groupings for Multi-Task Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Privacy-Preserving Wireless Federated Learning Exploiting Inherent Hardware Impairments.
Proceedings of the 26th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, 2021

A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer.
Proceedings of the Algorithmic Learning Theory, 2021

2020
Tempered Bregman Divergence for Continuous and Discrete Time Mirror Descent and Robust Classification.
PhD thesis, 2020

Measuring and Harnessing Transference in Multi-Task Learning.
CoRR, 2020

A case where a spindly two-layer linear network whips any neural network with a fully connected input layer.
CoRR, 2020

Interpolating Between Gradient Descent and Exponentiated Gradient Using Reparameterized Gradient Descent.
CoRR, 2020

Divergence-Based Motivation for Online EM and Combining Hidden Variable Models.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Reparameterizing Mirror Descent as Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Rank-Smoothed Pairwise Learning In Perceptual Quality Assessment.
Proceedings of the IEEE International Conference on Image Processing, 2020

Winnowing with Gradient Descent.
Proceedings of the Conference on Learning Theory, 2020

An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
TriMap: Large-scale Dimensionality Reduction Using Triplets.
CoRR, 2019

Robust Bi-Tempered Logistic Loss Based on Bregman Divergences.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Two-temperature logistic regression based on the Tsallis divergence.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A more globally accurate dimensionality reduction method using triplets.
CoRR, 2018

2017
Two-temperature logistic regression based on the Tsallis divergence.
CoRR, 2017

2016
t-Exponential Triplet Embedding.
CoRR, 2016

Semi-supervised Kernel Metric Learning Using Relative Comparisons.
CoRR, 2016

2015
Optimizing the Information Retrieval Trade-off in Data Visualization Using $α$-Divergence.
CoRR, 2015

A Kernel-Learning Approach to Semi-supervised Clustering with Relative Distance Comparisons.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Multiview Triplet Embedding: Learning Attributes in Multiple Maps.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Unsupervised feature extraction for multimedia event detection and ranking using audio content.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
PicSOM Experiments in TRECVID 2013.
Proceedings of the 2013 TREC Video Retrieval Evaluation, 2013

Bayesian Non-parametric Image Segmentation with Markov Random Field Prior.
Proceedings of the Image Analysis, 18th Scandinavian Conference, 2013


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