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ORCIDSeyed Hamed Hassani
S. Hamed Hassani – Hamed Hassani
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- affiliation: University of Pennsylvania, USA
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2020 – today
- 2024
[j32]Mark Beliaev
, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Efficient and Robust Classification for Sparse Attacks. IEEE J. Sel. Areas Inf. Theory 5: 261-272 (2024)- [j31]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Binary Classification Under ℓ0 Attacks for General Noise Distribution. IEEE Trans. Inf. Theory 70(2): 1284-1299 (2024) - [j30]Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson:
Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity. Trans. Mach. Learn. Res. 2024 (2024) - [j29]Aritra Mitra, George J. Pappas, Hamed Hassani:
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c105]Arman Adibi, Nicolò Dal Fabbro, Luca Schenato, Sanjeev R. Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra:
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. AISTATS 2024: 2746-2754 - [c104]Arman Adibi, Aritra Mitra, Hamed Hassani:
Min-Max Optimization Under Delays. ACC 2024: 80-85 - [c103]Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher:
Adversarial Training Should Be Cast as a Non-Zero-Sum Game. ICLR 2024 - [c102]Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai:
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. ICML 2024 - [c101]Shayan Kiyani, George J. Pappas, Hamed Hassani:
Conformal Prediction with Learned Features. ICML 2024 - [c100]Kevin Kögler, Aleksandr Shevchenko, Hamed Hassani, Marco Mondelli:
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. ICML 2024 - [c99]Behrad Moniri, Donghwan Lee, Hamed Hassani, Edgar Dobriban:
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks. ICML 2024 - [i131]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Generalization Properties of Adversarial Training for 𝓁0-Bounded Adversarial Attacks. CoRR abs/2402.03576 (2024) - [i130]Kevin Kögler, Alexander Shevchenko, Hamed Hassani, Marco Mondelli:
Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. CoRR abs/2402.05013 (2024) - [i129]Arman Adibi, Nicolò Dal Fabbro, Luca Schenato, Sanjeev R. Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra:
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. CoRR abs/2402.11800 (2024) - [i128]Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas, Hamed Hassani, Yang Zhang, Eric Wong, Shiyu Chang:
Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing. CoRR abs/2402.16192 (2024) - [i127]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding. CoRR abs/2403.07320 (2024) - [i126]Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J. Zico Kolter:
Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. CoRR abs/2403.19103 (2024) - [i125]Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong:
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR abs/2404.01318 (2024) - [i124]Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia, Hamed Hassani, Insup Lee, Osbert Bastani, Edgar Dobriban:
Uncertainty in Language Models: Assessment through Rank-Calibration. CoRR abs/2404.03163 (2024) - [i123]Shayan Kiyani, George J. Pappas, Hamed Hassani:
Conformal Prediction with Learned Features. CoRR abs/2404.17487 (2024) - [i122]Behrad Moniri, Hamed Hassani:
Signal-Plus-Noise Decomposition of Nonlinear Spiked Random Matrix Models. CoRR abs/2405.18274 (2024) - [i121]Xinmeng Huang, Shuo Li, Edgar Dobriban, Osbert Bastani, Hamed Hassani, Dongsheng Ding:
One-Shot Safety Alignment for Large Language Models via Optimal Dualization. CoRR abs/2405.19544 (2024) - [i120]Mahdi Sabbaghi, George J. Pappas, Hamed Hassani, Surbhi Goel:
Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks. CoRR abs/2406.01895 (2024) - [i119]Patrick Chao, Edgar Dobriban, Hamed Hassani:
Watermarking Language Models with Error Correcting Codes. CoRR abs/2406.10281 (2024) - [i118]Behrad Moniri, Hamed Hassani, Edgar Dobriban:
Evaluating the Performance of Large Language Models via Debates. CoRR abs/2406.11044 (2024) - [i117]Shayan Kiyani, George J. Pappas, Hamed Hassani:
Length Optimization in Conformal Prediction. CoRR abs/2406.18814 (2024) - [i116]Hongyan Chang, Hamed Hassani, Reza Shokri:
Watermark Smoothing Attacks against Language Models. CoRR abs/2407.14206 (2024) - 2023
- [j28]Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban:
T-Cal: An Optimal Test for the Calibration of Predictive Models. J. Mach. Learn. Res. 24: 335:1-335:72 (2023) - [j27]Mohammad Fereydounian, Hamed Hassani, Mohammad Vahid Jamali, Hessam Mahdavifar:
Channel Coding at Low Capacity. IEEE J. Sel. Areas Inf. Theory 4: 351-362 (2023) - [j26]Mohammad Fereydounian, Aryan Mokhtari, Ramtin Pedarsani, Hamed Hassani:
Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach. IEEE Trans. Inf. Theory 69(11): 7317-7335 (2023) - [j25]Edgar Dobriban, Hamed Hassani, David Hong, Alexander Robey:
Provable Tradeoffs in Adversarially Robust Classification. IEEE Trans. Inf. Theory 69(12): 7793-7822 (2023) - [j24]Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari:
Straggler-Resilient Personalized Federated Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c98]Thomas T. C. K. Zhang, Bruce D. Lee, Hamed Hassani, Nikolai Matni:
Adversarial Tradeoffs in Robust State Estimation. ACC 2023: 4083-4089 - [c97]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
On a Relation Between the Rate-Distortion Function and Optimal Transport. Tiny Papers @ ICLR 2023 - [c96]Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri:
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. ICLR 2023 - [c95]Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani:
Demystifying Disagreement-on-the-Line in High Dimensions. ICML 2023: 19053-19093 - [c94]Aleksandr Shevchenko, Kevin Kögler, Hamed Hassani, Marco Mondelli:
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. ICML 2023: 31151-31209 - [c93]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Federated Neural Compression Under Heterogeneous Data. ISIT 2023: 525-530 - [c92]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Generalization Properties of Adversarial Training for -ℓ0 Bounded Adversarial Attacks. ITW 2023: 113-118 - [c91]Aritra Mitra, Hamed Hassani, George J. Pappas:
Linear Stochastic Bandits over a Bit-Constrained Channel. L4DC 2023: 1387-1399 - [c90]Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett:
Toward Certified Robustness Against Real-World Distribution Shifts. SaTML 2023: 537-553 - [i115]Aritra Mitra, George J. Pappas, Hamed Hassani:
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning. CoRR abs/2301.00944 (2023) - [i114]Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani:
Demystifying Disagreement-on-the-Line in High Dimensions. CoRR abs/2301.13371 (2023) - [i113]Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson:
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity. CoRR abs/2302.02212 (2023) - [i112]Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni:
Performance-Robustness Tradeoffs in Adversarially Robust Control and Estimation. CoRR abs/2305.16415 (2023) - [i111]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Federated Neural Compression Under Heterogeneous Data. CoRR abs/2305.16416 (2023) - [i110]Xinmeng Huang, Kan Xu, Donghwan Lee, Hamed Hassani, Hamsa Bastani, Edgar Dobriban:
Optimal Heterogeneous Collaborative Linear Regression and Contextual Bandits. CoRR abs/2306.06291 (2023) - [i109]Alexander Robey, Fabian Latorre, George J. Pappas, Hamed Hassani, Volkan Cevher:
Adversarial Training Should Be Cast as a Non-Zero-Sum Game. CoRR abs/2306.11035 (2023) - [i108]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
On a Relation Between the Rate-Distortion Function and Optimal Transport. CoRR abs/2307.00246 (2023) - [i107]Eric Lei, Yigit Berkay Uslu, Hamed Hassani, Shirin Saeedi Bidokhti:
Text + Sketch: Image Compression at Ultra Low Rates. CoRR abs/2307.01944 (2023) - [i106]Arman Adibi, Aritra Mitra, Hamed Hassani:
Min-Max Optimization under Delays. CoRR abs/2307.06886 (2023) - [i105]Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai:
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. CoRR abs/2307.06887 (2023) - [i104]Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri:
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. CoRR abs/2309.05505 (2023) - [i103]Alexander Robey, Eric Wong, Hamed Hassani, George J. Pappas:
SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks. CoRR abs/2310.03684 (2023) - [i102]Behrad Moniri, Donghwan Lee, Hamed Hassani, Edgar Dobriban:
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks. CoRR abs/2310.07891 (2023) - [i101]Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, Eric Wong:
Jailbreaking Black Box Large Language Models in Twenty Queries. CoRR abs/2310.08419 (2023) - [i100]Eric Lei, Arman Adibi, Hamed Hassani:
Score-Based Methods for Discrete Optimization in Deep Learning. CoRR abs/2310.09890 (2023) - [i99]Thomas Waite, Alexander Robey, Hamed Hassani, George J. Pappas, Radoslav Ivanov:
Data-Driven Modeling and Verification of Perception-Based Autonomous Systems. CoRR abs/2312.06848 (2023) - 2022
- [j23]Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani:
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity. IEEE J. Sel. Areas Inf. Theory 3(2): 197-205 (2022) - [j22]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding. IEEE J. Sel. Areas Inf. Theory 3(4): 674-686 (2022) - [j21]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model. SIAM J. Math. Data Sci. 4(1): 362-385 (2022) - [j20]Xingran Chen, Konstantinos Gatsis, Hamed Hassani, Shirin Saeedi Bidokhti:
Age of Information in Random Access Channels. IEEE Trans. Inf. Theory 68(10): 6548-6568 (2022) - [c89]Arman Adibi, Aryan Mokhtari, Hamed Hassani:
Minimax Optimization: The Case of Convex-Submodular. AISTATS 2022: 3556-3580 - [c88]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. AISTATS 2022: 7814-7840 - [c87]Anton Xue, Lars Lindemann, Alexander Robey, Hamed Hassani, George J. Pappas, Rajeev Alur:
Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks. CDC 2022: 3389-3396 - [c86]Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni:
Performance-Robustness Tradeoffs in Adversarially Robust Linear-Quadratic Control. CDC 2022: 3416-3423 - [c85]Arman Adibi, Aritra Mitra, George J. Pappas, Hamed Hassani:
Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. CDC 2022: 4179-4184 - [c84]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker Planck Equation. COLT 2022: 817-841 - [c83]Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani:
Adaptive Node Participation for Straggler-Resilient Federated Learning. ICASSP 2022: 8762-8766 - [c82]Mohammad Vahid Jamali, Mohammad Fereydounian, Hessam Mahdavifar, Hamed Hassani:
Low-Complexity Decoding of a Class of Reed-Muller Subcodes for Low-Capacity Channels. ICC 2022: 123-128 - [c81]Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro:
An Agnostic Approach to Federated Learning with Class Imbalance. ICLR 2022 - [c80]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do deep networks transfer invariances across classes? ICLR 2022 - [c79]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani:
Probabilistically Robust Learning: Balancing Average and Worst-case Performance. ICML 2022: 18667-18686 - [c78]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Neural Estimation of the Rate-Distortion Function for Massive Datasets. ISIT 2022: 608-613 - [c77]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Binary Classification Under ℓ0 Attacks for General Noise Distribution. ISIT 2022: 1731-1736 - [c76]Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Efficient and Robust Classification for Sparse Attacks. ISIT 2022: 3150-3155 - [c75]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. NeurIPS 2022 - [c74]Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf:
Probable Domain Generalization via Quantile Risk Minimization. NeurIPS 2022 - [c73]Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani:
Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints. NeurIPS 2022 - [c72]Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani:
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. NeurIPS 2022 - [i98]Hamed Hassani, Adel Javanmard:
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression. CoRR abs/2201.05149 (2022) - [i97]Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Efficient and Robust Classification for Sparse Attacks. CoRR abs/2201.09369 (2022) - [i96]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani:
Probabilistically Robust Learning: Balancing Average- and Worst-case Performance. CoRR abs/2202.01136 (2022) - [i95]Mohammad Vahid Jamali, Mohammad Fereydounian, Hessam Mahdavifar, Hamed Hassani:
Low-Complexity Decoding of a Class of Reed-Muller Subcodes for Low-Capacity Channels. CoRR abs/2202.03654 (2022) - [i94]Mohammad Fereydounian, Hamed Hassani, Javid Dadashkarimi, Amin Karbasi:
The Exact Class of Graph Functions Generated by Graph Neural Networks. CoRR abs/2202.08833 (2022) - [i93]Mohammad Fereydounian, Aryan Mokhtari, Ramtin Pedarsani, Hamed Hassani:
Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach. CoRR abs/2202.09398 (2022) - [i92]Aritra Mitra, Hamed Hassani, George J. Pappas:
Linear Stochastic Bandits over a Bit-Constrained Channel. CoRR abs/2203.01198 (2022) - [i91]Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban:
T-Cal: An optimal test for the calibration of predictive models. CoRR abs/2203.01850 (2022) - [i90]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Binary Classification Under 𝓁0 Attacks for General Noise Distribution. CoRR abs/2203.04855 (2022) - [i89]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do Deep Networks Transfer Invariances Across Classes? CoRR abs/2203.09739 (2022) - [i88]Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni:
Performance-Robustness Tradeoffs in Adversarially Robust Linear-Quadratic Control. CoRR abs/2203.10763 (2022) - [i87]Anton Xue, Lars Lindemann, Alexander Robey, Hamed Hassani, George J. Pappas, Rajeev Alur:
Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks. CoRR abs/2204.00846 (2022) - [i86]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding. CoRR abs/2204.01612 (2022) - [i85]Arman Adibi, Aritra Mitra, George J. Pappas, Hamed Hassani:
Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. CoRR abs/2204.03187 (2022) - [i84]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. CoRR abs/2205.13692 (2022) - [i83]Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani:
Collaborative Learning of Distributions under Heterogeneity and Communication Constraints. CoRR abs/2206.00707 (2022) - [i82]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker-Planck Equation. CoRR abs/2206.00860 (2022) - [i81]Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari:
Straggler-Resilient Personalized Federated Learning. CoRR abs/2206.02078 (2022) - [i80]Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani:
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. CoRR abs/2206.02834 (2022) - [i79]Haoze Wu, Teruhiro Tagomori, Alexander Robey, Fengjun Yang, Nikolai Matni, George J. Pappas, Hamed Hassani, Corina S. Pasareanu, Clark W. Barrett:
Toward Certified Robustness Against Real-World Distribution Shifts. CoRR abs/2206.03669 (2022) - [i78]Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf:
Probable Domain Generalization via Quantile Risk Minimization. CoRR abs/2207.09944 (2022) - [i77]Alexander Shevchenko, Kevin Kögler, Hamed Hassani, Marco Mondelli:
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. CoRR abs/2212.13468 (2022) - 2021
- [j19]Konstantinos Gatsis, Hamed Hassani, George J. Pappas:
Latency-Reliability Tradeoffs for State Estimation. IEEE Trans. Autom. Control. 66(3): 1009-1023 (2021) - [j18]Arman Fazeli, Hamed Hassani, Marco Mondelli, Alexander Vardy:
Binary Linear Codes With Optimal Scaling: Polar Codes With Large Kernels. IEEE Trans. Inf. Theory 67(9): 5693-5710 (2021) - [j17]Deepak S. Kalhan, Amrit Singh Bedi, Alec Koppel, Ketan Rajawat, Hamed Hassani, Abhishek K. Gupta, Adrish Banerjee:
Dynamic Online Learning via Frank-Wolfe Algorithm. IEEE Trans. Signal Process. 69: 932-947 (2021) - [c71]Aritra Mitra, Rayana H. Jaafar, George J. Pappas, Hamed Hassani:
Federated Learning with Incrementally Aggregated Gradients. CDC 2021: 775-782 - [c70]Aritra Mitra, Hamed Hassani, George J. Pappas:
Online Federated Learning. CDC 2021: 4083-4090 - [c69]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
Exploiting Shared Representations for Personalized Federated Learning. ICML 2021: 2089-2099 - [c68]Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Deep Reinforcement Learning for Active Target Tracking. ICRA 2021: 1825-1831 - [c67]Alexander Robey, Arman Adibi, Brent Schlotfeldt, Hamed Hassani, George J. Pappas:
Optimal Algorithms for Submodular Maximization with Distributed Constraints. L4DC 2021: 150-162 - [c66]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani, Alejandro Ribeiro:
Adversarial Robustness with Semi-Infinite Constrained Learning. NeurIPS 2021: 6198-6215 - [c65]Aritra Mitra, Rayana H. Jaafar, George J. Pappas, Hamed Hassani:
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients. NeurIPS 2021: 14606-14619 - [c64]Alexander Robey, George J. Pappas, Hamed Hassani:
Model-Based Domain Generalization. NeurIPS 2021: 20210-20229 - [i76]Aritra Mitra, Rayana H. Jaafar, George J. Pappas, Hamed Hassani:
Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity. CoRR abs/2102.07053 (2021) - [i75]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
Exploiting Shared Representations for Personalized Federated Learning. CoRR abs/2102.07078 (2021) - [i74]Alexander Robey, George J. Pappas, Hamed Hassani:
Model-Based Domain Generalization. CoRR abs/2102.11436 (2021) - [i73]