Huseyin A. Inan

Orcid: 0000-0001-7465-7214

According to our database1, Huseyin A. Inan authored at least 39 papers between 2012 and 2024.

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Bibliography

2024
Controllable Synthetic Clinical Note Generation with Privacy Guarantees.
CoRR, 2024

Differentially Private Training of Mixture of Experts Models.
CoRR, 2024

Differentially Private Synthetic Data via Foundation Model APIs 2: Text.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Privately Aligning Language Models with Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Planting and Mitigating Memorized Content in Predictive-Text Language Models.
CoRR, 2022

Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe.
CoRR, 2022

Active Data Pattern Extraction Attacks on Generative Language Models.
CoRR, 2022

Privacy Leakage in Text Classification: A Data Extraction Approach.
CoRR, 2022

Differentially Private Model Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When Does Differentially Private Learning Not Suffer in High Dimensions?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differentially Private Fine-tuning of Language Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Membership Inference on Word Embedding and Beyond.
CoRR, 2021

On Privacy and Confidentiality of Communications in Organizational Graphs.
CoRR, 2021

Privacy Regularization: Joint Privacy-Utility Optimization in Language Models.
CoRR, 2021

Privacy Analysis in Language Models via Training Data Leakage Report.
CoRR, 2021

Privacy Regularization: Joint Privacy-Utility Optimization in LanguageModels.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

2020
Sparse Combinatorial Group Testing.
IEEE Trans. Inf. Theory, 2020

rTop-k: A Statistical Estimation Approach to Distributed SGD.
IEEE J. Sel. Areas Inf. Theory, 2020

Strongly Explicit and Efficiently Decodable Probabilistic Group Testing.
Proceedings of the IEEE International Symposium on Information Theory, 2020

2019
On the Optimality of the Kautz-Singleton Construction in Probabilistic Group Testing.
IEEE Trans. Inf. Theory, 2019

Improving Semantic Parsing with Neural Generator-Reranker Architecture.
CoRR, 2019

A Group Testing Approach to Random Access for Short-Packet Communication.
Proceedings of the IEEE International Symposium on Information Theory, 2019

2018
Capacity of the Energy Harvesting Gaussian MAC.
IEEE Trans. Inf. Theory, 2018

Energy-limited Massive Random Access via Noisy Group Testing.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017
Stationary Point Characterization for a Class of BCA Algorithms.
IEEE Trans. Signal Process., 2017

Sparse Combinatorial Group Testing for Low-Energy Massive Random Access.
CoRR, 2017

Sparse group testing codes for low-energy massive random access.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016
Online power control for the energy harvesting multiple access channel.
Proceedings of the 14th International Symposium on Modeling and Optimization in Mobile, 2016

2015
A Convolutive Bounded Component Analysis Framework for Potentially Nonstationary Independent and/or Dependent Sources.
IEEE Trans. Signal Process., 2015

Convolutive Bounded Component Analysis Algorithms for Independent and Dependent Source Separation.
IEEE Trans. Neural Networks Learn. Syst., 2015

2014
An extended family of bounded component analysis algorithms.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013
Robust estimation in flat fading channels under bounded channel uncertainties.
Digit. Signal Process., 2013

Adaptive mixture methods based on Bregman divergences.
Digit. Signal Process., 2013

A Bounded Component Analysis approach for the separation of convolutive mixtures of dependent and independent sources.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Robust Estimation in Rayleigh Fading Channels Under Bounded Channel Uncertainties
CoRR, 2012

Adaptive mixture methods using Bregman divergences.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012


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