Gholamali Aminian

Orcid: 0000-0002-4761-0151

According to our database1, Gholamali Aminian authored at least 27 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Information-Theoretic Characterizations of Generalization Error for the Gibbs Algorithm.
IEEE Trans. Inf. Theory, January, 2024

Learning Algorithm Generalization Error Bounds via Auxiliary Distributions.
IEEE J. Sel. Areas Inf. Theory, 2024

Generalization Error of Graph Neural Networks in the Mean-field Regime.
CoRR, 2024

2023
On Neural Networks Fitting, Compression, and Generalization Behavior via Information-Bottleneck-like Approaches.
Entropy, July, 2023

Mean-field Analysis of Generalization Errors.
CoRR, 2023

On the Generalization Error of Meta Learning for the Gibbs Algorithm.
Proceedings of the IEEE International Symposium on Information Theory, 2023

How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Learning Algorithm Generalization Error Bounds via Auxiliary Distributions.
CoRR, 2022

Semi-Counterfactual Risk Minimization Via Neural Networks.
CoRR, 2022

Tighter Expected Generalization Error Bounds via Convexity of Information Measures.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information.
CoRR, 2021

An Exact Characterization of the Generalization Error for the Gibbs Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck.
Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms.
Proceedings of the IEEE International Symposium on Information Theory, 2021

2020
Jensen-Shannon Information Based Characterization of the Generalization Error of Learning Algorithms.
Proceedings of the IEEE Information Theory Workshop, 2020

2019
On Medium Chemical Reaction in Diffusion-Based Molecular Communication: A Two-Way Relaying Example.
IEEE Trans. Commun., 2019

2018
Diffusion-Based Molecular Communication With Limited Molecule Production Rate.
IEEE Trans. Mol. Biol. Multi Scale Commun., 2018

On the Capacity of a Class of Signal-Dependent Noise Channels.
IEEE Trans. Inf. Theory, 2018

2017
On the capacity of signal dependent noise channels.
Proceedings of the Iran Workshop on Communication and Information Theory, 2017

2016
Physical layer network coding in molecular two-way relay networks.
Proceedings of the Iran Workshop on Communication and Information Theory, 2016

2015
On the Capacity of Point-to-Point and Multiple-Access Molecular Communications With Ligand-Receptors.
IEEE Trans. Mol. Biol. Multi Scale Commun., 2015

Capacity of Diffusion-Based Molecular Communication Networks Over LTI-Poisson Channels.
IEEE Trans. Mol. Biol. Multi Scale Commun., 2015

On the Capacity of Level and Type Modulation in Molecular Communication with Ligand Receptors.
CoRR, 2015

On the capacity of level and type modulations in Molecular communication with ligand receptors.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Capacity of LTI-Poisson channel for diffusion based molecular communication.
Proceedings of the 2015 IEEE International Conference on Communications, 2015


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