Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDSeyed Hamed Hassani
S. Hamed Hassani – Hamed Hassani
Person information
- affiliation: University of Pennsylvania, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j24]Mohammad Fereydounian
, Hamed Hassani, Mohammad Vahid Jamali, Hessam Mahdavifar:
Channel Coding at Low Capacity. IEEE J. Sel. Areas Inf. Theory 4: 351-362 (2023)- [c96]Thomas T. C. K. Zhang, Bruce D. Lee, Hamed Hassani, Nikolai Matni:
Adversarial Tradeoffs in Robust State Estimation. ACC 2023: 4083-4089 - [c95]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
On a Relation Between the Rate-Distortion Function and Optimal Transport. Tiny Papers @ ICLR 2023 - [c94]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 - [c93]Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani:
Demystifying Disagreement-on-the-Line in High Dimensions. ICML 2023: 19053-19093 - [c92]Aleksandr Shevchenko, Kevin Kögler, Hamed Hassani, Marco Mondelli:
Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. ICML 2023: 31151-31209 - [c91]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Federated Neural Compression Under Heterogeneous Data. ISIT 2023: 525-530 - [c90]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Generalization Properties of Adversarial Training for -ℓ0 Bounded Adversarial Attacks. ITW 2023: 113-118 - [c89]Aritra Mitra, Hamed Hassani, George J. Pappas:
Linear Stochastic Bandits over a Bit-Constrained Channel. L4DC 2023: 1387-1399 - [i110]Aritra Mitra, George J. Pappas, Hamed Hassani:
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning. CoRR abs/2301.00944 (2023) - [i109]Donghwan Lee, Behrad Moniri, Xinmeng Huang, Edgar Dobriban, Hamed Hassani:
Demystifying Disagreement-on-the-Line in High Dimensions. CoRR abs/2301.13371 (2023) - [i108]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) - [i107]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) - [i106]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Federated Neural Compression Under Heterogeneous Data. CoRR abs/2305.16416 (2023) - [i105]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) - [i104]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) - [i103]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
On a Relation Between the Rate-Distortion Function and Optimal Transport. CoRR abs/2307.00246 (2023) - [i102]Eric Lei, Yigit Berkay Uslu, Hamed Hassani, Shirin Saeedi Bidokhti:
Text + Sketch: Image Compression at Ultra Low Rates. CoRR abs/2307.01944 (2023) - [i101]Arman Adibi, Aritra Mitra, Hamed Hassani:
Min-Max Optimization under Delays. CoRR abs/2307.06886 (2023) - [i100]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) - [i99]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) - 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) - [c88]Arman Adibi, Aryan Mokhtari, Hamed Hassani:
Minimax Optimization: The Case of Convex-Submodular. AISTATS 2022: 3556-3580 - [c87]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. AISTATS 2022: 7814-7840 - [c86]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 - [c85]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 - [c84]Arman Adibi, Aritra Mitra, George J. Pappas, Hamed Hassani:
Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. CDC 2022: 4179-4184 - [c83]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker Planck Equation. COLT 2022: 817-841 - [c82]Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani:
Adaptive Node Participation for Straggler-Resilient Federated Learning. ICASSP 2022: 8762-8766 - [c81]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 - [c80]Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro:
An Agnostic Approach to Federated Learning with Class Imbalance. ICLR 2022 - [c79]Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn:
Do deep networks transfer invariances across classes? ICLR 2022 - [c78]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani:
Probabilistically Robust Learning: Balancing Average and Worst-case Performance. ICML 2022: 18667-18686 - [c77]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Neural Estimation of the Rate-Distortion Function for Massive Datasets. ISIT 2022: 608-613 - [c76]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Binary Classification Under ℓ0 Attacks for General Noise Distribution. ISIT 2022: 1731-1736 - [c75]Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Efficient and Robust Classification for Sparse Attacks. ISIT 2022: 3150-3155 - [c74]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. NeurIPS 2022 - [c73]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 - [c72]Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani:
Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints. NeurIPS 2022 - [c71]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) - [c70]Aritra Mitra, Rayana H. Jaafar, George J. Pappas, Hamed Hassani:
Federated Learning with Incrementally Aggregated Gradients. CDC 2021: 775-782 - [c69]Aritra Mitra, Hamed Hassani, George J. Pappas:
Online Federated Learning. CDC 2021: 4083-4090 - [c68]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
Exploiting Shared Representations for Personalized Federated Learning. ICML 2021: 2089-2099 - [c67]Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Deep Reinforcement Learning for Active Target Tracking. ICRA 2021: 1825-1831 - [c66]Alexander Robey, Arman Adibi, Brent Schlotfeldt, Hamed Hassani, George J. Pappas:
Optimal Algorithms for Submodular Maximization with Distributed Constraints. L4DC 2021: 150-162 - [c65]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani, Alejandro Ribeiro:
Adversarial Robustness with Semi-Infinite Constrained Learning. NeurIPS 2021: 6198-6215 - [c64]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 - [c63]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]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. CoRR abs/2103.06972 (2021) - [i72]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Robust Classification Under 𝓁0 Attack for the Gaussian Mixture Model. CoRR abs/2104.02189 (2021) - [i71]Francisco Barreras, Mikhail Hayhoe, Hamed Hassani, Victor M. Preciado:
AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data. CoRR abs/2106.14357 (2021) - [i70]Aritra Mitra, Hamed Hassani, George J. Pappas:
Exploiting Heterogeneity in Robust Federated Best-Arm Identification. CoRR abs/2109.05700 (2021) - [i69]Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti:
Out-of-Distribution Robustness in Deep Learning Compression. CoRR abs/2110.07007 (2021) - [i68]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani, Alejandro Ribeiro:
Adversarial Robustness with Semi-Infinite Constrained Learning. CoRR abs/2110.15767 (2021) - [i67]Arman Adibi, Aryan Mokhtari, Hamed Hassani:
Minimax Optimization: The Case of Convex-Submodular. CoRR abs/2111.01262 (2021) - [i66]Bruce D. Lee, Thomas T. C. K. Zhang, Hamed Hassani, Nikolai Matni:
Adversarial Tradeoffs in Linear Inverse Problems and Robust State Estimation. CoRR abs/2111.08864 (2021) - 2020
- [j16]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. J. Mach. Learn. Res. 21: 105:1-105:49 (2020) - [j15]Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen:
Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. SIAM J. Optim. 30(4): 3315-3344 (2020) - [c62]Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi:
Black Box Submodular Maximization: Discrete and Continuous Settings. AISTATS 2020: 1058-1070 - [c61]Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani:
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization. AISTATS 2020: 2021-2031 - [c60]Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free. AISTATS 2020: 3696-3706 - [c59]Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
One Sample Stochastic Frank-Wolfe. AISTATS 2020: 4012-4023 - [c58]Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani:
Precise Tradeoffs in Adversarial Training for Linear Regression. COLT 2020: 2034-2078 - [c57]Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani:
Quantized Decentralized Stochastic Learning over Directed Graphs. ICML 2020: 9324-9333 - [c56]Xingran Chen, Konstantinos Gatsis, Hamed Hassani, Shirin Saeedi Bidokhti:
Age of Information in Random Access Channels. ISIT 2020: 1770-1775 - [c55]Arman Adibi, Aryan Mokhtari, Hamed Hassani:
Submodular Meta-Learning. NeurIPS 2020 - [c54]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Barycenter via Functional Gradient Descent. NeurIPS 2020 - [c53]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Natural Gradient for Generative Models. NeurIPS 2020 - [i65]Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani:
Quantized Push-sum for Gossip and Decentralized Optimization over Directed Graphs. CoRR abs/2002.09964 (2020) - [i64]Adel Javanmard, Mahdi Soltanolkotabi, Hamed Hassani:
Precise Tradeoffs in Adversarial Training for Linear Regression. CoRR abs/2002.10477 (2020) - [i63]Alexander Robey, Hamed Hassani, George J. Pappas:
Model-Based Robust Deep Learning. CoRR abs/2005.10247 (2020) - [i62]Edgar Dobriban, Hamed Hassani, David Hong, Alexander Robey:
Provable tradeoffs in adversarially robust classification. CoRR abs/2006.05161 (2020) - [i61]Heejin Jeong, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Learning to Track Dynamic Targets in Partially Known Environments. CoRR abs/2006.10190 (2020) - [i60]Mohammad Fereydounian, Zebang Shen, Aryan Mokhtari, Amin Karbasi, Hamed Hassani:
Safe Learning under Uncertain Objectives and Constraints. CoRR abs/2006.13326 (2020) - [i59]Arman Adibi, Aryan Mokhtari, Hamed Hassani:
Submodular Meta-Learning. CoRR abs/2007.05852 (2020) - [i58]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Barycenter via Functional Gradient Descent. CoRR abs/2007.10449 (2020) - [i57]Zebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani:
Sinkhorn Natural Gradient for Generative Models. CoRR abs/2011.04162 (2020) - [i56]Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani:
Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity. CoRR abs/2012.14453 (2020)
2010 – 2019
- 2019
- [j14]Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke:
A New Coding Paradigm for the Primitive Relay Channel. Algorithms 12(10): 218 (2019) - [j13]Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke:
Construction of Polar Codes With Sublinear Complexity. IEEE Trans. Inf. Theory 65(5): 2782-2791 (2019) - [j12]Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani:
An Exact Quantized Decentralized Gradient Descent Algorithm. IEEE Trans. Signal Process. 67(19): 4934-4947 (2019) - [c52]Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi:
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. ICML 2019: 414-423 - [c51]Zebang Shen, Alejandro Ribeiro, Hamed Hassani, Hui Qian, Chao Mi:
Hessian Aided Policy Gradient. ICML 2019: 5729-5738 - [c50]Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Learning Q-network for Active Information Acquisition. IROS 2019: 6822-6827 - [c49]Mohammad Fereydounian, Xingran Chen, Hamed Hassani, Shirin Saeedi Bidokhti:
Non-asymptotic Coded Slotted ALOHA. ISIT 2019: 111-115 - [c48]Mohammad Fereydounian, Mohammad Vahid Jamali, Hamed Hassani, Hessam Mahdavifar:
Channel Coding at Low Capacity. ITW 2019: 1-5 - [c47]Amirhossein Reisizadeh, Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani:
Robust and Communication-Efficient Collaborative Learning. NeurIPS 2019: 8386-8397 - [c46]Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. NeurIPS 2019: 9206-9217 - [c45]Mahyar Fazlyab, Alexander Robey, Hamed Hassani, Manfred Morari, George J. Pappas:
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks. NeurIPS 2019: 11423-11434 - [c44]