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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
- 2022
[j20]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)- [c75]Arman Adibi, Aryan Mokhtari, Hamed Hassani:
Minimax Optimization: The Case of Convex-Submodular. AISTATS 2022: 3556-3580 - [c74]Zebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi:
Federated Functional Gradient Boosting. AISTATS 2022: 7814-7840 - [c73]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker Planck Equation. COLT 2022: 817-841 - [c72]Amirhossein Reisizadeh, Isidoros Tziotis, Hamed Hassani, Aryan Mokhtari, Ramtin Pedarsani:
Adaptive Node Participation for Straggler-Resilient Federated Learning. ICASSP 2022: 8762-8766 - [c71]Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani:
Probabilistically Robust Learning: Balancing Average and Worst-case Performance. ICML 2022: 18667-18686 - [i97]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) - [i96]Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Efficient and Robust Classification for Sparse Attacks. CoRR abs/2201.09369 (2022) - [i95]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) - [i94]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) - [i93]Mohammad Fereydounian, Hamed Hassani, Javid Dadashkarimi, Amin Karbasi:
The Exact Class of Graph Functions Generated by Graph Neural Networks. CoRR abs/2202.08833 (2022) - [i92]Mohammad Fereydounian, Aryan Mokhtari, Ramtin Pedarsani, Hamed Hassani:
Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach. CoRR abs/2202.09398 (2022) - [i91]Aritra Mitra, Hamed Hassani, George J. Pappas:
Linear Stochastic Bandits over a Bit-Constrained Channel. CoRR abs/2203.01198 (2022) - [i90]Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban:
T-Cal: An optimal test for the calibration of predictive models. CoRR abs/2203.01850 (2022) - [i89]Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Binary Classification Under 𝓁0 Attacks for General Noise Distribution. CoRR abs/2203.04855 (2022) - [i88]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) - [i87]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) - [i86]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) - [i85]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) - [i84]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) - [i83]Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai:
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. CoRR abs/2205.13692 (2022) - [i82]Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani:
Collaborative Learning of Distributions under Heterogeneity and Communication Constraints. CoRR abs/2206.00707 (2022) - [i81]Zebang Shen, Zhenfu Wang, Satyen Kale, Alejandro Ribeiro, Amin Karbasi, Hamed Hassani:
Self-Consistency of the Fokker-Planck Equation. CoRR abs/2206.00860 (2022) - [i80]Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari:
Straggler-Resilient Personalized Federated Learning. CoRR abs/2206.02078 (2022) - [i79]Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani:
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. CoRR abs/2206.02834 (2022) - [i78]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) - [i77]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) - 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]Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen:
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. NeurIPS 2019: 13066-13076 - [i55]Lin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi:
Black Box Submodular Maximization: Discrete and Continuous Settings. CoRR abs/1901.09515 (2019) - [i54]Mingrui Zhang, Lin Chen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization. CoRR abs/1902.06332 (2019) - [i53]Hamed Hassani, Amin Karbasi, Aryan Mokhtari, Zebang Shen:
Stochastic Conditional Gradient++. CoRR abs/1902.06992 (2019) - [i52]Mahyar Fazlyab, Alexander Robey, Hamed Hassani, Manfred Morari, George J. Pappas:
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks. CoRR abs/1906.04893 (2019) - [i51]Amirhossein Reisizadeh, Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani:
Robust and Communication-Efficient Collaborative Learning. CoRR abs/1907.10595 (2019) - [i50]Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ali Jadbabaie, Ramtin Pedarsani:
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization. CoRR abs/1909.13014 (2019) - [i49]Alexander Robey, Arman Adibi, Brent Schlotfeldt, George J. Pappas, Hamed Hassani:
Optimal Algorithms for Submodular Maximization with Distributed Constraints. CoRR abs/1909.13676 (2019) - [i48]Mingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
One Sample Stochastic Frank-Wolfe. CoRR abs/1910.04322 (2019) - [i47]Heejin Jeong, Brent Schlotfeldt, Hamed Hassani, Manfred Morari, Daniel D. Lee, George J. Pappas:
Learning Q-network for Active Information Acquisition. CoRR abs/1910.10754 (2019) - [i46]Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. CoRR abs/1910.12424 (2019) - [i45]Xingran Chen, Konstantinos Gatsis, Hamed Hassani, Shirin Saeedi Bidokhti:
Age of Information in Random Access Channels. CoRR abs/1912.01473 (2019) - 2018
- [j11]Seyyed Ali Hashemi, Marco Mondelli, S. Hamed Hassani, Carlo Condo, Rüdiger L. Urbanke, Warren J. Gross:
Decoder Partitioning: Towards Practical List Decoding of Polar Codes. IEEE Trans. Commun. 66(9): 3749-3759 (2018) - [j10]Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke:
How to Achieve the Capacity of Asymmetric Channels. IEEE Trans. Inf. Theory 64(5): 3371-3393 (2018) - [c43]Adish Singla, Seyed Hamed Hassani, Andreas Krause:
Learning to Interact With Learning Agents. AAAI 2018: 4083-4090 - [c42]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. AISTATS 2018: 1886-1895 - [c41]Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization. AISTATS 2018: 1896-1905 - [c40]Amirhossein Reisizadeh, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani:
Quantized Decentralized Consensus Optimization. CDC 2018: 5838-5843 - [c39]Lin Chen, Christopher Harshaw, Hamed Hassani, Amin Karbasi:
Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity. ICML 2018: 813-822 - [c38]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings. ICML 2018: 3613-3622 - [c37]S. Hamed Hassani, Shrinivas Kudekar, Or Ordentlich, Yury Polyanskiy, Rüdiger L. Urbanke:
Almost Optimal Scaling of Reed-Muller Codes on BEC and BSC Channels. ISIT 2018: 311-315 - [c36]Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke:
A New Coding Paradigm for the Primitive Relay Channel. ISIT 2018: 351-355 - [c35]Arman Fazeli, S. Hamed Hassani, Marco Mondelli, Alexander Vardy:
Binary Linear Codes with Optimal Scaling: Polar Codes with Large Kernels. ITW 2018: 1-5 - [c34]Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka:
Discrete Sampling using Semigradient-based Product Mixtures. UAI 2018: 229-237 - [i44]Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke:
A New Coding Paradigm for the Primitive Relay Channel. CoRR abs/1801.03153 (2018) - [i43]S. Hamed Hassani, Shrinivas Kudekar, Or Ordentlich, Yury Polyanskiy, Rüdiger L. Urbanke:
Almost Optimal Scaling of Reed-Muller Codes on BEC and BSC Channels. CoRR abs/1801.09481 (2018) - [i42]Lin Chen, Hamed Hassani, Amin Karbasi:
Online Continuous Submodular Maximization. CoRR abs/1802.06052 (2018) - [i41]Aryan Mokhtari, Hamed Hassani, Amin Karbasi:
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. CoRR abs/1804.09554 (2018) - [i40]Amirhossein Reisizadeh, Aryan Mokhtari, S. Hamed Hassani, Ramtin Pedarsani:
Quantized Decentralized Consensus Optimization. CoRR abs/1806.11536 (2018) - [i39]Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka:
Discrete Sampling using Semigradient-based Product Mixtures. CoRR abs/1807.01808 (2018) - [i38]Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi:
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. CoRR abs/1810.04147 (2018) - [i37]Konstantinos Gatsis, Hamed Hassani, George J. Pappas:
Latency-Reliability Tradeoffs for State Estimation. CoRR abs/1810.11831 (2018) - [i36]Mikhail Hayhoe, Francisco Barreras, Hamed Hassani, Victor M. Preciado:
SPECTRE: Seedless Network Alignment via Spectral Centralities. CoRR abs/1811.01056 (2018) - [i35]Mohammad Fereydounian, Mohammad Vahid Jamali, Hamed Hassani, Hessam Mahdavifar:
Channel Coding at Low Capacity. CoRR abs/1811.04322 (2018) - 2017
- [c33]Lin Chen, Seyed Hamed Hassani, Amin Karbasi:
Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting. AAAI 2017: 1798-1804 - [c32]Yuxin Chen, Seyed Hamed Hassani, Andreas Krause:
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. AISTATS 2017: 223-231 - [c31]Seyyed Ali Hashemi, Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke, Warren J. Gross:
Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance. GLOBECOM 2017: 1-7 - [c30]Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Uniform Deviation Bounds for k-Means Clustering. ICML 2017: 283-291 - [c29]Dimitris Achlioptas, S. Hamed Hassani, Wei Liu, Rüdiger L. Urbanke:
Time-invariant LDPC convolutional codes. ISIT 2017: 366-370 - [c28]Marco Mondelli, S. Hamed Hassani, Rüdiger L. Urbanke:
Construction of polar codes with sublinear complexity. ISIT 2017: 1853-1857 - [c27]S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi:
Gradient Methods for Submodular Maximization. NIPS 2017: 5841-5851 - [c26]Mohammad Reza Karimi, Mario Lucic, S. Hamed Hassani, Andreas Krause:
Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS 2017: 6853-6863 - [c25]Marco Mondelli, S. Hamed Hassani, Ivana Maric, Dennis Hui,