Adaptive mixture methods using Bregman divergences. - Huseyin A. Inan; Mehmet A. Donmez; Suleyman Serdar Kozat (ICASSP, 2012)

Robust Estimation in Rayleigh Fading Channels Under Bounded Channel Uncertainties - Mehmet A. Donmez; Huseyin A. Inan; Suleyman Serdar Kozat (CoRR, 2012)

A Bounded Component Analysis approach for the separation of convolutive mixtures of dependent and independent sources. - Huseyin A. Inan; Alper T. Erdogan (ICASSP, 2013)

Adaptive mixture methods based on Bregman divergences. - Mehmet A. Donmez; Huseyin A. Inan; Suleyman Serdar Kozat (Digit. Signal Process., 2013)

Robust estimation in flat fading channels under bounded channel uncertainties. - Mehmet A. Donmez; Huseyin A. Inan; Suleyman Serdar Kozat (Digit. Signal Process., 2013)

An extended family of bounded component analysis algorithms. - Huseyin A. Inan; Alper T. Erdogan (ACSSC, 2014)

Convolutive Bounded Component Analysis Algorithms for Independent and Dependent Source Separation. - Huseyin A. Inan; Alper T. Erdogan (IEEE Trans. Neural Networks Learn. Syst., 2015)

A Convolutive Bounded Component Analysis Framework for Potentially Nonstationary Independent and/or Dependent Sources. - Huseyin A. Inan; Alper T. Erdogan (IEEE Trans. Signal Process., 2015)

Online power control for the energy harvesting multiple access channel. - Huseyin A. Inan; Ayfer Özgür (WiOpt, 2016)

Sparse group testing codes for low-energy massive random access. - Huseyin A. Inan; Peter Kairouz; Ayfer Özgür (Allerton, 2017)

Sparse Combinatorial Group Testing for Low-Energy Massive Random Access. - Huseyin A. Inan; Peter Kairouz; Ayfer Özgür (CoRR, 2017)

Stationary Point Characterization for a Class of BCA Algorithms. - Huseyin A. Inan; Alper T. Erdogan; Sergio Cruces (IEEE Trans. Signal Process., 2017)

Energy-limited Massive Random Access via Noisy Group Testing. - Huseyin A. Inan; Peter Kairouz; Ayfer Özgür (ISIT, 2018)

Capacity of the Energy Harvesting Gaussian MAC. - Huseyin A. Inan; Dor Shaviv; Ayfer Özgür (IEEE Trans. Inf. Theory, 2018)

A Group Testing Approach to Random Access for Short-Packet Communication. - Huseyin A. Inan; Surin Ahn; Peter Kairouz; Ayfer Özgür (ISIT, 2019)

Improving Semantic Parsing with Neural Generator-Reranker Architecture. - Huseyin A. Inan; Gaurav Singh Tomar; Huapu Pan (CoRR, 2019)

On the Optimality of the Kautz-Singleton Construction in Probabilistic Group Testing. - Huseyin A. Inan; Peter Kairouz; Mary Wootters; Ayfer Özgür (IEEE Trans. Inf. Theory, 2019)

Strongly Explicit and Efficiently Decodable Probabilistic Group Testing. - Huseyin A. Inan; Ayfer Özgür (ISIT, 2020)

rTop-k: A Statistical Estimation Approach to Distributed SGD. - Leighton Pate Barnes; Huseyin A. Inan; Berivan Isik; Ayfer Özgür (IEEE J. Sel. Areas Inf. Theory, 2020)

Sparse Combinatorial Group Testing. - Huseyin A. Inan; Peter Kairouz; Ayfer Özgür (IEEE Trans. Inf. Theory, 2020)

Privacy Regularization: Joint Privacy-Utility Optimization in LanguageModels. - Fatemehsadat Mireshghallah; Huseyin A. Inan; Marcello Hasegawa; Victor Rühle; Taylor Berg-Kirkpatrick; Robert Sim (NAACL-HLT, 2021)

Privacy Analysis in Language Models via Training Data Leakage Report. - Huseyin A. Inan; Osman Ramadan; Lukas Wutschitz; Daniel Jones; Victor Rühle; James Withers; Robert Sim (CoRR, 2021)

Privacy Regularization: Joint Privacy-Utility Optimization in Language Models. - Fatemehsadat Mireshghallah; Huseyin A. Inan; Marcello Hasegawa; Victor Rühle; Taylor Berg-Kirkpatrick; Robert Sim (CoRR, 2021)

On Privacy and Confidentiality of Communications in Organizational Graphs. - Masoumeh Shafieinejad; Huseyin A. Inan; Marcello Hasegawa; Robert Sim (CoRR, 2021)

Membership Inference on Word Embedding and Beyond. - Saeed Mahloujifar; Huseyin A. Inan; Melissa Chase; Esha Ghosh; Marcello Hasegawa (CoRR, 2021)

When Does Differentially Private Learning Not Suffer in High Dimensions? - Xuechen Li 005; Daogao Liu; Tatsunori B. Hashimoto; Huseyin A. Inan; Janardhan Kulkarni; Yin Tat Lee; Abhradeep Guha Thakurta (NeurIPS, 2022)

Differentially Private Model Compression. - Fatemehsadat Mireshghallah; Arturs Backurs; Huseyin A. Inan; Lukas Wutschitz; Janardhan Kulkarni (NeurIPS, 2022)

Privacy Leakage in Text Classification: A Data Extraction Approach. - Adel Elmahdy; Huseyin A. Inan; Robert Sim (CoRR, 2022)

Active Data Pattern Extraction Attacks on Generative Language Models. - Bargav Jayaraman; Esha Ghosh; Huseyin A. Inan; Melissa Chase; Sambuddha Roy; Wei Dai 007 (CoRR, 2022)

Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe. - Xiang Yue; Huseyin A. Inan; Xuechen Li; Girish Kumar; Julia McAnallen; Huan Sun 001; David Levitan; Robert Sim (CoRR, 2022)

Planting and Mitigating Memorized Content in Predictive-Text Language Models. - C. M. Downey; Wei Dai 007; Huseyin A. Inan; Kim Laine; Saurabh Naik; Tomasz Religa (CoRR, 2022)

Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe. - Xiang Yue; Huseyin A. Inan; Xuechen Li; Girish Kumar; Julia McAnallen; Hoda Shajari; Huan Sun 001; David Levitan; Robert Sim (ACL (1), 2023)

Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks. - Ruixiang Tang; Gord Lueck; Rodolfo Quispe; Huseyin A. Inan; Janardhan Kulkarni; Xia Hu 001 (EMNLP (Findings), 2023)

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation. - Xinyu Tang 003; Richard Shin; Huseyin A. Inan; Andre Manoel; Fatemehsadat Mireshghallah; Zinan Lin 001; Sivakanth Gopi; Janardhan Kulkarni; Robert Sim (ICLR, 2024)

Privately Aligning Language Models with Reinforcement Learning. - Fan Wu; Huseyin A. Inan; Arturs Backurs; Varun Chandrasekaran; Janardhan Kulkarni; Robert Sim (ICLR, 2024)

Differentially Private Synthetic Data via Foundation Model APIs 2: Text. - Chulin Xie; Zinan Lin 001; Arturs Backurs; Sivakanth Gopi; Da Yu; Huseyin A. Inan; Harsha Nori; Haotian Jiang; Huishuai Zhang; Yin Tat Lee; Bo Li 026; Sergey Yekhanin (ICML, 2024)

Differentially Private Training of Mixture of Experts Models. - Pierre Tholoniat; Huseyin A. Inan; Janardhan Kulkarni; Robert Sim (CoRR, 2024)

Controllable Synthetic Clinical Note Generation with Privacy Guarantees. - Tal Baumel; Andre Manoel; Daniel Jones; Shize Su; Huseyin A. Inan; Aaron Bornstein; Robert Sim (CoRR, 2024)

Differentially Private Fine-tuning of Language Models. - Da Yu; Saurabh Naik; Arturs Backurs; Sivakanth Gopi; Huseyin A. Inan; Gautam Kamath 001; Janardhan Kulkarni; Yin Tat Lee; Andre Manoel; Lukas Wutschitz; Sergey Yekhanin; Huishuai Zhang (J. Priv. Confidentiality, 2024)

On the Emergence of Thinking in LLMs I: Searching for the Right Intuition. - Guanghao Ye; Khiem Duc Pham; Xinzhi Zhang 002; Sivakanth Gopi; Baolin Peng; Beibin Li; Janardhan Kulkarni; Huseyin A. Inan (CoRR, 2025)

Contextual Integrity in LLMs via Reasoning and Reinforcement Learning. - Guangchen Lan; Huseyin A. Inan; Sahar Abdelnabi; Janardhan Kulkarni; Lukas Wutschitz; Reza Shokri; Christopher G. Brinton; Robert Sim (CoRR, 2025)