Hamed Hassani
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
51
Venues
13
Active years
2018–2026
Best venue rank
A*
Where they publish
Papers
51 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities. | Changdae Oh, Seongheon Park, To Eun Kim, Jiatong Li, Wendi Li, Samuel Yeh, Sean Du, Hamed Hassani, Paul Bogdan, Dawn Song, Sharon Li |
| 2025 | EMNLP | Adaptively profiling models with task elicitation. | Davis Brown, Prithvi Balehannina, Helen Jin, Shreya Havaldar, Hamed Hassani, Eric Wong |
| 2025 | EMNLP | Watermark Smoothing Attacks against Language Models. | Hongyan Chang, Hamed Hassani, Reza Shokri |
| 2025 | ICLR | Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding. | Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2025 | ICML | Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents. | Shayan Kiyani, George J. Pappas, Aaron Roth, Hamed Hassani |
| 2025 | ICML | Adversarial Reasoning at Jailbreaking Time. | Mahdi Sabbaghi, Paul Kassianik, George J. Pappas, Amin Karbasi, Hamed Hassani |
| 2025 | ICML | On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning. | Thomas T. C. K. Zhang, Behrad Moniri, Ansh Nagwekar, Faraz Rahman, Anton Xue, Hamed Hassani, Nikolai Matni |
| 2025 | IJCNLP | Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing. | Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang |
| 2025 | ICRA | Jailbreaking LLM-Controlled Robots. | Alexander Robey, Zachary Ravichandran, Vijay Kumar, Hamed Hassani, George J. Pappas |
| 2025 | NAACL | Evaluating the Performance of Large Language Models via Debates. | Behrad Moniri, Hamed Hassani, Edgar Dobriban |
| 2024 | AISTATS | Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. | Arman Adibi, Nicol Dal Fabbro, Luca Schenato, Sanjeev R. Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra |
| 2024 | EMNLP | Uncertainty in Language Models: Assessment through Rank-Calibration. | Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia, Hamed Hassani, Insup Lee, Osbert Bastani, Edgar Dobriban |
| 2024 | ICLR | Adversarial Training Should Be Cast as a Non-Zero-Sum Game. | Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher |
| 2024 | ICML | Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. | Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai |
| 2024 | ICML | Conformal Prediction with Learned Features. | Shayan Kiyani, George J. Pappas, Hamed Hassani |
| 2024 | ICML | Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. | Kevin Kgler, Aleksandr Shevchenko, Hamed Hassani, Marco Mondelli |
| 2024 | ICML | A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks. | Behrad Moniri, Donghwan Lee, Hamed Hassani, Edgar Dobriban |
| 2023 | ICLR | On a Relation Between the Rate-Distortion Function and Optimal Transport. | Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2023 | ICLR | Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. | Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri |
| 2023 | ICML | Demystifying Disagreement-on-the-Line in High Dimensions. | Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani |
| 2023 | ICML | Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. | Aleksandr Shevchenko, Kevin Kgler, Hamed Hassani, Marco Mondelli |
| 2023 | ISIT | Federated Neural Compression Under Heterogeneous Data. | Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2023 | ITW | Generalization Properties of Adversarial Training for -ℓ0 Bounded Adversarial Attacks. | Payam Delgosha, Hamed Hassani, Ramtin Pedarsani |
| 2022 | AISTATS | Minimax Optimization: The Case of Convex-Submodular. | Arman Adibi, Aryan Mokhtari, Hamed Hassani |
| 2022 | AISTATS | Federated Functional Gradient Boosting. | Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi |
| 2022 | COLT | Self-Consistency of the Fokker Planck Equation. | Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani |
| 2022 | ICASSP | Adaptive Node Participation for Straggler-Resilient Federated Learning. | Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani |
| 2022 | ICLR | An Agnostic Approach to Federated Learning with Class Imbalance. | Zebang Shen, Juan Cervio, Hamed Hassani, Alejandro Ribeiro |
| 2022 | ICLR | Do deep networks transfer invariances across classes? | Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn |
| 2022 | ICML | Probabilistically Robust Learning: Balancing Average and Worst-case Performance. | Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani |
| 2022 | ISIT | Efficient and Robust Classification for Sparse Attacks. | Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani |
| 2022 | ISIT | Binary Classification Under ℓ0 Attacks for General Noise Distribution. | Payam Delgosha, Hamed Hassani, Ramtin Pedarsani |
| 2022 | ISIT | Neural Estimation of the Rate-Distortion Function for Massive Datasets. | Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2021 | ICML | Exploiting Shared Representations for Personalized Federated Learning. | Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai |
| 2021 | ICRA | Deep Reinforcement Learning for Active Target Tracking. | Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas |
| 2020 | AISTATS | Black Box Submodular Maximization: Discrete and Continuous Settings. | Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi |
| 2020 | AISTATS | FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization. | Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani |
| 2020 | AISTATS | Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free. | Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi |
| 2020 | AISTATS | One Sample Stochastic Frank-Wolfe. | Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi |
| 2020 | COLT | Precise Tradeoffs in Adversarial Training for Linear Regression. | Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani |
| 2020 | ICML | Quantized Decentralized Stochastic Learning over Directed Graphs. | Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani |
| 2020 | ISIT | Age of Information in Random Access Channels. | Xingran Chen, Konstantinos Gatsis, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2019 | ICML | Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. | Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi |
| 2019 | ICML | Hessian Aided Policy Gradient. | Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi |
| 2019 | IROS | Learning Q-network for Active Information Acquisition. | Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas |
| 2019 | ISIT | Non-asymptotic Coded Slotted ALOHA. | Mohammad Fereydounian, Xingran Chen, Hamed Hassani, Shirin Saeedi Bidokhti |
| 2019 | ITW | Channel Coding at Low Capacity. | Mohammad Fereydounian, Mohammad Vahid Jamali, Hamed Hassani, Hessam Mahdavifar |
| 2018 | AISTATS | Online Continuous Submodular Maximization. | Lin Chen, Hamed Hassani, Amin Karbasi |
| 2018 | AISTATS | Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. | Aryan Mokhtari, Hamed Hassani, Amin Karbasi |
| 2018 | ICML | Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity. | Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi |
| 2018 | ICML | Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings. | Aryan Mokhtari, Hamed Hassani, Amin Karbasi |