Preprints
J. Kang, R. Pedarsani, K. Ramchandran, “The Fair Value of Data Under Heterogeneous Privacy Constraints”, Submitted.
M. Fereydounian, A. Mokhtari, R. Pedarsani, H. Hassani, “Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach”, Submitted.
B. Toghi, R. Valiente, R. Pedarsani, Y. Fallah, “Towards Learning Generalizable Driving Policies from Restricted Latent Representations”, Submitted.
I. Tziotis, Z. Shen, R. Pedarsani, H. Hassani, A. Mokhtari, “Straggler-Resilient Personalized Federated Learning”, Submitted.
Journal Publications
A. Reisizadeh, I. Tziotis, H. Hassani, A. Mokhtari, R. Pedarsani, “Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity”, IEEE Journal on Selected Areas in Information Theory, 2022.
B. Puranik, U. Madhow, R. Pedarsani, “Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis Testing”, IEEE Transactions on Signal Processing (TSP), 2022.
F. Farnia, A. Reisizadeh, R. Pedarsani, A. Jadbabaie, “An Optimal Transport Approach to Personalized Federated Learning”, IEEE Journal on Selected Areas in Information Theory, 2022.
B. Toghi, R. Valiente, D. Sadigh, R. Pedarsani, Y. Fallah, “Social Coordination and Altruism in Cooperative Autonomous Driving”, IEEE Transactions on Intelligent Transportation Systems (TITS), 2022.
R. Valiente, B. Toghi, R. Pedarsani, Y. Fallah, “Robustness and Adaptability of Reinforcement Learning based Cooperative Autonomous Driving in Mixed-autonomy Traffic”, Accepted to appear in IEEE Open Journal of Intelligent Transportation Systems, 2022.
P. Delgosha, H. Hassani, R. Pedarsani, “Robust Classification Under l0 Attack for the Gaussian Mixture Model”, SIAM Journal on Mathematics of Data Science (SIMODS), Vol. 4, No. 1, 2022.
A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “CodedReduce: A Fast and Robust Framework for Gradient Aggregation in Distributed Learning”, IEEE Transactions on Networking, Vol. 30, No. 1, 2022.
D. Lazar, E. Biyik, D. Sadigh, and R. Pedarsani, “Learning How to Dynamically Route Autonomous Vehicles on Shared Roads", Journal of Transportation Research Part C, Vol. 130, 2021.
C. Yang, R. Pedarsani, S. Avestimehr, “Edge Computing in the Dark: Leveraging Contextual-Combinatorial Bandit and Coded Computing”, IEEE/ACM Transactions on Networking (ToN), Vol. 29, No. 3, 2021.
H. Taheri, R. Pedarsani, C. Thrampoulidis, “Sharp Guarantees and Optimal Performance for Inference in Binary and Gaussian-mixture Models”, Entropy: Special Issue on the Role of Signal Processing and Information Theory in Modern Machine Learning, Vol. 23, No. 2, 2021.
E. Biyik, D. Lazar, R. Pedarsani, D. Sadigh “Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy", IEEE Transactions on Control of Network Systems (TCNS), Vol. 8, No. 4, 2021.
D. Lazar and R. Pedarsani, “Optimal Tolling for Multitype Mixed Autonomous Traffic Networks”, IEEE Control Systems Letters, Vol. 5, No. 5, 2021.
D. Lazar, S. Coogan, and R. Pedarsani, “Routing for Traffic Networks with Mixed Autonomy”,
IEEE Transactions on Automatic Control (TAC), Vol. 66, No. 6, 2021.
B. Turan, R. Pedarsani, M. Alizadeh, “Dynamic Pricing and Fleet Management for Electric Autonomous Mobility on Demand Systems”, Journal of Transportation Research Part C, Vol. 121, 2020.
S. Prakash, A. Reisizadeh, R. Pedarsani, S. Avestimehr, "Coded Computing for Distributed Graph Analytics”,
IEEE Transactions on Information Theory, Vol. 66, No. 10, 2020.
Q. Wei, J. R. Pedarsani, S. Coogan, “Mixed Autonomy in Ride-Sharing Networks”, IEEE Transactions on Control of Network Systems (TCNS), Vol. 7, No. 4, 2020.
A. Reisizadeh, A. Mokhtari, H. Hassani, R. Pedarsani, “An Exact Quantized Decentralized Gradient Descent Algorithm”,
IEEE Transactions on Signal Processing (TSP), Vol. 67, No. 19, 2019.
C. Yang, R. Pedarsani, S. Avestimehr, “Communication-Aware Scheduling of Serial Tasks for Dispersed Computing”,
IEEE/ACM Transactions on Networking, Vol. 27, No. 4, 2019.
A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “Coded Computation over Heterogeneous Clusters”, IEEE Transactions on Information Theory, Vol. 65, No. 7, 2019.
X. Li, D. Yin, S. Pawar, R. Pedarsani, and K. Ramchandran, “Sub-linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes”, IEEE Transactions on Information Theory, Vol. 65, No. 10, 2019.
K. Lee, K. Chandrasekher, R. Pedarsani, and K. Ramchandran, “SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on Sparse-Graph Codes”,
Vol. 67, No. 17, IEEE Transactions on Signal Processing, 2019.
D. Yin, R. Pedarsani, Y. Chen, and K. Ramchandran, “Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes”, IEEE Transactions on Information Theory, Vol. 65, No. 3, 2019.
K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding Up Distributed Machine Learning Using Codes”,
IEEE Transactions on Information Theory, Vol. 64, No. 3, 2018. (Joint Comm/IT Society Paper Award)
R. Pedarsani, K. Lee, and K. Ramchandran, “PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph Codes”,
IEEE Transactions on Information Theory, Vol. 63, No. 6, 2017.
R. Pedarsani, J. Walrand, and Yuan Zhong, “Robust Scheduling for Flexible Processing Networks”,
Advances in Applied Probability, Vol. 49, No. 2, 2017.
J. Lioris, R. Pedarsani, F. Yildiz, and P. Varaiya, “Platoons of Connected Vehicles Can Double Throughput in Urban Roads”,
Journal of Transportation Research Part C, vol. 75, pp. 292-305, 2017.
R. Pedarsani and J. Walrand, “Stability of Open Multiclass Queueing Networks under Longest-Queue
and Longest-Dominating-Queue Scheduling”, Journal of Applied Probability, Vol. 53, No. 2, 2016.
R. Pedarsani, M. Maddah-Ali, and U. Niesen, “Online Coded Caching”, IEEE/ACM Transactions on Networking, Vol. 24, No. 2, 2016.
A. Muralidharan, R. Pedarsani, and P. Varaiya, “Analysis of Fixed-Time Control”,
Journal of Transportation Research Part B, vol. 73, pp. 81–90, 2015.
K. Lee, R. Pedarsani, and K. Ramchandran, “On Scheduling Redundant Requests with Cancellation Overheads”,
IEEE/ACM Transactions on Networking, Vol. 25, No. 2, pp. 1279–1290, 2017.
R. Pedarsani, O. Leveque, and S. Yang, “On the DMT Optimality of Time-Varying Distributed Rotation over Slow Fading Relay Channels”,
IEEE Transactions on Wireless Communication, vol. 14, pp. 421–434, 2015.
CS Conference Publications
Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee, “Equal Improvability: A New Fairness Notion Considering the Long-Term Impact”, International Conference on Learning Representations (ICLR), 2023.
M. Beliaev, A. Shih, S. Ermon, D. Sadigh, R. Pedarsani, “Imitation Learning by Estimating Expertise of Demonstrators”, International Conference on Machine Learning (ICML), 2022.
B. Puranik, U. Madhow, R. Pedarsani, “A Dynamic Decision-Making Framework Promoting Long-Term Fairness”, AAAI/ACM Conference on Artificial Intelligent, Ethics, and Society (AIES), 2022.
W. Wang, M. Beliaev, E. Biyik, D. Lazar, R. Pedarsani, and D. Sadigh, “Emergent Prosociality in Multi-Agent Games Through Gifting”, International Joint Conference on Artificial Intelligence (IJCAI), 2021.
H. Taheri, R. Pedarsani, C. Thrampoulidis, “Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions”, International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
M. Beliaev, E. Biyik, D. Lazar, W. Wang, D. Sadigh, and R. Pedarsani, “Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic”, ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2021.
A. Reisizadeh, F. Farnia, R. Pedarsani, A. Jadbabaie, “Robust Federated Learning: The Case of Affine Distribution Shifts”, Advances in Neural Information Processing Systems (NeurIPS), 2020.
H. Taheri, A. Mokhtari, H. Hassani, R. Pedarsani, “Quantized Decentralized Stochastic Learning over Directed Graphs”, International Conference on Machine Learning (ICML), 2020.
A. Reisizadeh, A. Mokhtari, H. Hassani, A. Jadbabaie, R. Pedarsani, “FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization”, International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
H. Taheri, R. Pedarsani, C. Thrampoulidis, “Sharp Asymptotics and Optimal Performance for Inference in Binary Models”, International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
A. Reisizadeh, H. Taheri, A. Mokhtari, H. Hassani, R. Pedarsani, “Robust and Communication-Efficient Collaborative Learning”, Advances in Neural Information Processing Systems (NeurIPS), 2019.
C. Yang, R. Pedarsani, S. Avestimehr, “Timely-Throughput Optimal Coded Computing over Cloud Networks”, ACM International Symposium on Mobile Ad Hoc Networking and Computing (Mobihoc), 2019. (Best Paper Award Finalist)
E. Biyik, D. Lazar, R. Pedarsani, D. Sadigh , “Altruistic Autonomy: Beating Congestion on Shared Roads”,
13th International Workshop on Algorithmic Foundations of Robotics (WAFR), 2018.
Conference Publications
P. Delgosha, H. Hassani, R. Pedarsani, “Binary Classification Under l0 Attacks for General Noise Distribution”, IEEE International Symposium on Information Theory (ISIT), 2022.
M. Beliaev, P. Delgosha, H. Hassani, R. Pedarsani, “Efficient and Robust Classification for Sparse Attacks”, IEEE International Symposium on Information Theory (ISIT), 2022.
H. Taheri, R. Pedarsani, C. Thrampoulidis, “Asymptotic Behavior of Adversarial Training in Binary Classification”, IEEE International Symposium on Information Theory (ISIT), 2022.
B. Puranik, U. Madhow, R. Pedarsani, “Dynamic Positive Reinforcement for Long-Term Fairness”, International Conference on Learning Representations (ICLR) 2022 Workshop on Socially Responsible Machine Learning.
A. Reisizadeh, I. Tziotis, H. Hassani, A. Mokhtari, R. Pedarsani, “Adaptive Node Participation for Straggler-resilient Federated Learning”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.
M. Beliaev, N. Mehr, R. Pedarsani, “Congestion-aware Bi-modal Delivery Systems Utilizing Drones”, European Control Conference (ECC), 2022.
D. Lazar, R. Pedarsani, “Anonymous Tolling for Traffic Networks with Mixed Autonomy”, European Control Conference (ECC), 2022.
B. Toghi, R. Valiente, D. Sadigh, R. Pedarsani, Y. Fallah, “Cooperative Autonomous Vehicles that Sympathize with Human Drivers”, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
B. Toghi, R. Valiente, D. Sadigh, R. Pedarsani, Y. Fallah, “Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic”, 2021 ADP3 Workshop at IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
B. Puranik, U. Madhow, R. Pedarsani, “Adversarially Robust Classification Based on GLRT”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021.
M. Beliaev, W. Wang, D. Lazar, E. Biyik, D. Sadigh, and R. Pedarsani, “Emergent Correlated Equilibrium through Synchronized Exploration”, Robotics: Science and Systems (RSS) Workshop on Emergent Behaviors in Human-Robot Systems, 2020.
S. Prakash, A. Reisizadeh, R. Pedarsani, S. Avestimehr, “Hierarchical Coded Gradient Aggregation for Learning at the Edge”, IEEE International Symposium on Information Theory (ISIT), 2020.
H. Taheri, R. Pedarsani, C. Thrampoulidis, “Optimality of Least-squares for Classification in Gaussian-Mixture Models”, IEEE International Symposium on Information Theory (ISIT), 2020.
C. Yang, R. Pedarsani, S. Avestimehr, “Coded Computing in Unknown Environment via Online Learning”, IEEE International Symposium on Information Theory (ISIT), 2020.
C. Bakiskan, S. Gopalakrishnan, M. Cekic, U. Madhow, R. Pedarsani, “Polarizing Front Ends for Robust CNNs”, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.
D. Lazar, E. Biyik, D. Sadigh, and R. Pedarsani, “The Green Choice: Learning and Influencing Human Decisions on Shared Roads", IEEE Conference on Decision and Control (CDC), 2019.
D. Lazar, S. Coogan, and R. Pedarsani, “Optimal Tolling for Heterogeneous Traffic Networks with Mixed Autonomy”, IEEE Conference on Decision and Control (CDC), 2019.
H. Taheri, R. Pedarsani, C. Thrampoulidis, “Sharp Guarantees for Solving Random Equations with One-Bit Information”, Allerton Conference on Communication, Control, and Computing, 2019.
A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “Tree Gradient Coding”,
IEEE International Symposium on Information Theory (ISIT), 2019.
C. Yang, R. Pedarsani, S. Avestimehr, “Timely Coded Computing”,
IEEE International Symposium on Information Theory (ISIT), 2019.
Q. Wei, J. A. Rodriguez, R. Pedarsani, S. Coogan, “Ride-Sharing Networks with Mixed Autonomy”,
IEEE American Control Conference (ACC), 2019.
A. Reisizadeh, A. Mokhtari, H. Hassani, R. Pedarsani, “Quantized Decentralized Consensus Optimization”,
IEEE Conference on Decision and Control (CDC), 2018.
D. Lazar, K. Chandrasekher, R. Pedarsani, and D. Sadigh, “Maximizing Road Capacity Using Cars that Influence People”,
IEEE Conference on Decision and Control (CDC), 2018.
S. Gopalakrishnan, Z. Marzi, U. Madhow, and R. Pedarsani, “Combating Adversarial Attacks Using Sparse Representation”,
International Conference on Learning Representations (ICLR) Workshop track, 2018.
A. Reisizadeh, P. Abdalla, R. Pedarsani, “Sub-linear Time Stochastic Threshold Group Testing via Sparse-Graph Codes”, Information Theory Workshop (ITW), 2018.
N. Mehr, R. Horowtiz, and R. Pedarsani, “Signal Control for Urban Traffic Networks with Unknown System Parameters”, IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018.
Z. Marzi, S. Gopalakrishnan, U. Madhow, R. Pedarsani, “Sparsity-based Defense against
Adversarial Attacks on Linear Classifiers”, IEEE International Symposium on Information Theory (ISIT), 2018.
C. Yang, R. Pedarsani, S. Avestimehr, “Communication-Aware Scheduling of Serial Tasks for Dispersed Computing”,
IEEE International Symposium on Information Theory (ISIT), 2018.
S. Prakash, A. Reisizadeh, R. Pedarsani, S. Avestimehr, “Coded Computing for Distributed Graph Analytics”,
IEEE International Symposium on Information Theory (ISIT), 2018.
D. Lazar, S. Coogan, and R. Pedarsani, “The Price of Anarchy for Transportation Networks with Mixed Autonomy”,
IEEE American Control Conference (ACC), 2018.
D. Lazar, S. Coogan, and R. Pedarsani, “Capacity Modeling and Routing for Traffic Networks with Mixed Autonomy”,
IEEE Conference on Decision and Control (CDC), 2017.
N. Mehr, R. Horowtiz, and R. Pedarsani, “Low-Complexity Ramp Metering for Freeway Congestion Control via
Network Utility Maximization”, IEEE Conference on Decision and Control (CDC), 2017.
P. Abdalla, A. Reisizadeh, R. Pedarsani, “Multilevel Group Testing via Sparse-graph Codes”,
Asilomar Conference on Signals, Systems, and Computers, 2017.
A. Reisizadeh, R. Pedarsani, “Latency Analysis of Coded Computation Schemes over Wireless Networks”,
Allerton Conference on Communication, Control, and Computing, 2017.
D. Yin, R. Pedarsani, Y. Chen, and K. Ramchandran, “Learning Mixtures of Sparse Linear Regressions Using Sparse Graph Codes”,
Allerton Conference on Communication, Control, and Computing, 2017.
N. Mehr, J. Lioris, R. Horowtiz, and R. Pedarsani, “Joint Perimeter and Signal Control of Urban Traffic via Network Utility Maximization”,
IEEE International Conference on Intelligent Transportation Systems (ITSC), 2017.
A. Reisizadeh, S. Prakash, R. Pedarsani, S. Avestimehr, “Coded Computation over Heterogeneous Clusters”,
IEEE International Symposium on Information Theory (ISIT), 2017.
K. Lee, R. Pedarsani, D. Papailiopoulos, K. Ramchandran, “Coded Computation for Multicore Setups”,
IEEE International Symposium on Information Theory (ISIT), 2017.
K. Chandrasekher, K. Lee, P. Kairouz, R. Pedarsani, and K. Ramchandran, “Asynchronous and Noncoherent Neighbor
Discovery for the IoT Using Sparse-Graph Codes”, IEEE International Conference on Communications (ICC), 2017.
J. Chung, K. Lee, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “UberShuffle: Communication-efficient
Data Shuffling for SGD via Coding Theory”, Neural Information Processing Systems (NeurIPS): Workshop on Machine Learning Systems, 2017.
D. Yin, R. Pedarsani, X. Li, and K. Ramchandran, “Fast and Robust Support Recovery for Compressive Sensing with
Continuous Alphabet”, Allerton Conference on Communications, Control and Computing, 2016.
Z. Amini, R. Pedarsani, A. Skabardonis, and P. Varaiya, “Queue-Length Estimation Using Real-Time Traffic Data”,
IEEE International Conference on Intelligent Transportation Systems (ITSC), 2016.
K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding Up Distributed Machine Learning Using Codes”,
IEEE International Symposium on Information Theory (ISIT), 2016.
K. Lee, R. Pedarsani, and K. Ramchandran, “SAFFRON: A Fast, Efficient, and Robust Framework for Group Testing based on
Sparse-Graph Codes”, IEEE International Symposium on Information Theory (ISIT), 2016.
J. Lioris, R. Pedarsani, F. Yildiz, and P. Varaiya, “Doubling Throughput in Urban Roads by Platooning”,
IFAC Symposium on Control in Transportation Systems, 2015.
K. Lee, M. Lam, R. Pedarsani, D. Papailiopoulos, and K. Ramchandran, “Speeding Up Distributed Machine Learning Using Codes”, Neural Information Processing Systems (NeuIPS): Workshop on Machine Learning Systems, 2015.
R. Pedarsani, K. Lee, and K. Ramchandran, “Sparse Covariance Estimation Based on Sparse-Graph Codes”,
Allerton Conference on Communication, Control and Computing, 2015.
K. Lee, R. Pedarsani, and K. Ramchandran, “On Scheduling Redundant Requests with Cancellation Overheads”,
Allerton Conference on Communication, Control and Computing, 2015.
R. Pedarsani, K. Lee, and K. Ramchandran, “Capacity-Approaching PhaseCode for Low-Complexity Compressive Phase Retrieval”,
IEEE International Symposium on Information Theory (ISIT), 2015. (arxiv version)
D. Yin, K. Lee, R. Pedarsani, and K. Ramchandran, “Fast and Robust Compressive Phase Retrieval with Sparse-Graph Codes”,
IEEE International Symposium on Information Theory (ISIT), 2015.
R. Pedarsani, J. Walrand, and Y. Zhong, “Scheduling Tasks with Precedence Constraints on Multiple Servers”,
Allerton Conference on Communication, Control, and Computing, 2014.
R. Pedarsani, K. Lee, and K. Ramchandran, “PhaseCode: Fast and Efficient Compressive Phase Retrieval based on Sparse-Graph Codes”,
Allerton Conference on Communication, Control, and Computing, 2014.
R. Pedarsani, J. Walrand, and Y. Zhong, “Robust Scheduling in a Flexible Fork-Join Network”,
IEEE Conference on Decision and Control (CDC), 2014.
R. Pedarsani, M. Maddah-Ali, and U. Niesen, “Online Coded Caching”,
IEEE International Conference on Communications (ICC), 2014. (Best paper award)
R. Pedarsani, J. Walrand, and Y. Zhong, “Robust Scheduling and Congestion Control for Flexible Queueing Networks”,
IEEE International Conference on Computing, Networking and Communications (ICNC), 2014.
R. Pedarsani, S. H. Hassani, I. Tal, and E. Telatar, “On the Construction of Polar Codes”,
IEEE International Symposium on Information Theory (ISIT), 2011.
R. Pedarsani, O. Leveque, and S. Yang, “On the DMT Optimality of the Rotate-and-Forward Scheme in a Two-Hop MIMO Relay Channel”,
Allerton Conference on Communication, Control, and Computing, 2010.
R. Pedarsani, O. Leveque, and S. Yang, “Flip-and-forward Achieves the Optimal Diversity-Multiplexing Tradeoff for the Two-Hop MIMO Relay Channel, with Two Relay Antennas”,
Fifth International Conference on Cognitive Radio Oriented Wireless Network and Communications (CROWNCOM), 2010.
Patents
Theses
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