A New (t, n) Multi-Secret Sharing Scheme Based on Linear Algebra. - Seyed Hamed Hassani; Mohammad Reza Aref (SECRYPT, 2006)

Non-Saturation Mode Analysis of IEEE 802.11 MAC Protocol. - Seyed Hamed Hassani; Farid Ashtiani; Pouya Tehrani (PIMRC, 2007)

The compound capacity of polar codes. - S. Hamed Hassani; Satish Babu Korada; Rüdiger L. Urbanke (Allerton, 2009)

On the scaling of polar codes: II. The behavior of un-polarized channels. - Seyed Hamed Hassani; Kasra Alishahi; Rüdiger L. Urbanke (ISIT, 2010)

On the scaling of polar codes: I. The behavior of polarized channels. - Seyed Hamed Hassani; Rüdiger L. Urbanke (ISIT, 2010)

Coupled graphical models and their thresholds. - S. Hamed Hassani; Nicolas Macris; Rüdiger L. Urbanke (ITW, 2010)

Near concavity of the growth rate for coupled LDPC chains. - Seyed Hamed Hassani; Nicolas Macris; Ryuhei Mori (ISIT, 2011)

On the construction of polar codes. - Ramtin Pedarsani; Seyed Hamed Hassani; Ido Tal; Emre Telatar (ISIT, 2011)

Chains of Mean Field Models - Seyed Hamed Hassani; Nicolas Macris; Rüdiger L. Urbanke (CoRR, 2011)

Threshold Saturation in Spatially Coupled Constraint Satisfaction Problems - Seyed Hamed Hassani; Nicolas Macris; Rüdiger L. Urbanke (CoRR, 2011)

Universal bounds on the scaling behavior of polar codes. - Ali Goli; Seyed Hamed Hassani; Rüdiger L. Urbanke (ISIT, 2012)

Polar codes: Robustness of the successive cancellation decoder with respect to quantization. - Seyed Hamed Hassani; Rüdiger L. Urbanke (ISIT, 2012)

The space of solutions of coupled XORSAT formulae. - Seyed Hamed Hassani; Nicolas Macris; Rüdiger L. Urbanke (ISIT, 2013)

The least degraded and the least upgraded channel with respect to a channel family. - Wei Liu 105; Seyed Hamed Hassani; Rüdiger L. Urbanke (ITW, 2013)

Extended polar codes perform better in terms of compound rate and scaling behavior. - S. Hamed Hassani (IWCIT, 2013)

Rate-Dependent Analysis of the Asymptotic Behavior of Channel Polarization. - Seyed Hamed Hassani; Ryuhei Mori; Toshiyuki Tanaka; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2013)

Polarization and Spatial Coupling - Two Techniques to Boost Performance. - Seyed Hamed Hassani (2013)

Universal polar codes. - Seyed Hamed Hassani; Rüdiger L. Urbanke (ISIT, 2014)

Achieving the Superposition and Binning Regions for Broadcast Channels Using Polar Codes. - Marco Mondelli; Seyed Hamed Hassani; Igal Sason; Rüdiger L. Urbanke (CoRR, 2014)

From Polar to Reed-Muller Codes: A Technique to Improve the Finite-Length Performance. - Marco Mondelli; Seyed Hamed Hassani; Rüdiger L. Urbanke (IEEE Trans. Commun., 2014)

Finite-Length Scaling for Polar Codes. - Seyed Hamed Hassani; Kasra Alishahi; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2014)

Sequential Information Maximization: When is Greedy Near-optimal? - Yuxin Chen 001; S. Hamed Hassani; Amin Karbasi; Andreas Krause 001 (COLT, 2015)

Sampling from Probabilistic Submodular Models. - Alkis Gotovos; S. Hamed Hassani; Andreas Krause 001 (NIPS, 2015)

Growing a Graph Matching from a Handful of Seeds. - Ehsan Kazemi 001; Seyed Hamed Hassani; Matthias Grossglauser (Proc. VLDB Endow., 2015)

Achieving Marton's Region for Broadcast Channels Using Polar Codes. - Marco Mondelli; Seyed Hamed Hassani; Igal Sason; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2015)

Scaling Exponent of List Decoders With Applications to Polar Codes. - Marco Mondelli; Seyed Hamed Hassani; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2015)

Approximate K-Means++ in Sublinear Time. - Olivier Bachem; Mario Lucic; S. Hamed Hassani; Andreas Krause 001 (AAAI, 2016)

Fast and Provably Good Seedings for k-Means. - Olivier Bachem; Mario Lucic; Seyed Hamed Hassani; Andreas Krause 001 (NIPS, 2016)

Bounds for Random Constraint Satisfaction Problems via Spatial Coupling. - Dimitris Achlioptas; Seyed Hamed Hassani; Nicolas Macris; Rüdiger L. Urbanke (SODA, 2016)

PROPER: global protein interaction network alignment through percolation matching. - Ehsan Kazemi 001; Seyed Hamed Hassani; Matthias Grossglauser; Hassan Pezeshgi Modarres (BMC Bioinform., 2016)

Dimension Coupling: Optimal Active Learning of Halfspaces via Query Synthesis. - Lin Chen 003; S. Hamed Hassani; Amin Karbasi (CoRR, 2016)

Alignment of Polarized Sets. - Joseph M. Renes; David Sutter; Seyed Hamed Hassani (IEEE J. Sel. Areas Commun., 2016)

Unified Scaling of Polar Codes: Error Exponent, Scaling Exponent, Moderate Deviations, and Error Floors. - Marco Mondelli; S. Hamed Hassani; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2016)

Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting. - Lin Chen 003; Seyed Hamed Hassani; Amin Karbasi (AAAI, 2017)

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. - Yuxin Chen 001; Seyed Hamed Hassani; Andreas Krause 001 (AISTATS, 2017)

Partitioned List Decoding of Polar Codes: Analysis and Improvement of Finite Length Performance. - Seyyed Ali Hashemi; Marco Mondelli; S. Hamed Hassani; Rüdiger L. Urbanke; Warren J. Gross (GLOBECOM, 2017)

Uniform Deviation Bounds for k-Means Clustering. - Olivier Bachem; Mario Lucic; S. Hamed Hassani; Andreas Krause 001 (ICML, 2017)

Time-invariant LDPC convolutional codes. - Dimitris Achlioptas; S. Hamed Hassani; Wei Liu 105; Rüdiger L. Urbanke (ISIT, 2017)

Gradient Methods for Submodular Maximization. - S. Hamed Hassani; Mahdi Soltanolkotabi; Amin Karbasi (NIPS, 2017)

Stochastic Submodular Maximization: The Case of Coverage Functions. - Mohammad Reza Karimi; Mario Lucic; S. Hamed Hassani; Andreas Krause 001 (NIPS, 2017)

Capacity-Achieving Rate-Compatible Polar Codes for General Channels. - Marco Mondelli; S. Hamed Hassani; Ivana Maric; Dennis Hui; Song-Nam Hong 001 (WCNC Workshops, 2017)

Uniform Deviation Bounds for Unbounded Loss Functions like k-Means. - Olivier Bachem; Mario Lucic; S. Hamed Hassani; Andreas Krause 001 (CoRR, 2017)

Accelerated Dual Learning by Homotopic Initialization. - Hadi Daneshmand; Hamed Hassani; Thomas Hofmann 001 (CoRR, 2017)

Learning to Use Learners' Advice. - Adish Singla; Seyed Hamed Hassani; Andreas Krause 001 (CoRR, 2017)

Binary Linear Codes with Optimal Scaling and Quasi-Linear Complexity. - Arman Fazeli; S. Hamed Hassani; Marco Mondelli; Alexander Vardy (CoRR, 2017)

Learning to Interact With Learning Agents. - Adish Singla; Seyed Hamed Hassani; Andreas Krause 001 (AAAI, 2018)

Online Continuous Submodular Maximization. - Lin Chen 003; Hamed Hassani; Amin Karbasi (AISTATS, 2018)

Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap. - Aryan Mokhtari; Hamed Hassani; Amin Karbasi (AISTATS, 2018)

Quantized Decentralized Consensus Optimization. - Amirhossein Reisizadeh; Aryan Mokhtari; Hamed Hassani; Ramtin Pedarsani (CDC, 2018)

Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity. - Lin Chen 003; Christopher Harshaw; Hamed Hassani; Amin Karbasi (ICML, 2018)

Decentralized Submodular Maximization: Bridging Discrete and Continuous Settings. - Aryan Mokhtari; Hamed Hassani; Amin Karbasi (ICML, 2018)

Almost Optimal Scaling of Reed-Muller Codes on BEC and BSC Channels. - S. Hamed Hassani; Shrinivas Kudekar; Or Ordentlich; Yury Polyanskiy; Rüdiger L. Urbanke (ISIT, 2018)

Discrete Sampling using Semigradient-based Product Mixtures. - Alkis Gotovos; S. Hamed Hassani; Andreas Krause 001; Stefanie Jegelka (UAI, 2018)

SPECTRE: Seedless Network Alignment via Spectral Centralities. - Mikhail Hayhoe; Francisco Barreras; Hamed Hassani; Victor M. Preciado (CoRR, 2018)

Decoder Partitioning: Towards Practical List Decoding of Polar Codes. - Seyyed Ali Hashemi; Marco Mondelli; S. Hamed Hassani; Carlo Condo; Rüdiger L. Urbanke; Warren J. Gross (IEEE Trans. Commun., 2018)

How to Achieve the Capacity of Asymmetric Channels. - Marco Mondelli; S. Hamed Hassani; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2018)

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. - Yogesh Balaji; Hamed Hassani; Rama Chellappa; Soheil Feizi (ICML, 2019)

Hessian Aided Policy Gradient. - Zebang Shen; Alejandro Ribeiro; Hamed Hassani; Hui Qian 001; Chao Mi (ICML, 2019)

Learning Q-network for Active Information Acquisition. - Heejin Jeong; Brent Schlotfeldt; Hamed Hassani; Manfred Morari; Daniel D. Lee; George J. Pappas (IROS, 2019)

Non-asymptotic Coded Slotted ALOHA. - Mohammad Fereydounian; Xingran Chen; Hamed Hassani; Shirin Saeedi Bidokhti (ISIT, 2019)

Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks. - Mahyar Fazlyab; Alexander Robey; Hamed Hassani; Manfred Morari; George J. Pappas (NeurIPS, 2019)

Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match. - Amin Karbasi; Hamed Hassani; Aryan Mokhtari; Zebang Shen (NeurIPS, 2019)

Robust and Communication-Efficient Collaborative Learning. - Amirhossein Reisizadeh; Hossein Taheri; Aryan Mokhtari; Hamed Hassani; Ramtin Pedarsani (NeurIPS, 2019)

Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback. - Mingrui Zhang; Lin Chen 003; Hamed Hassani; Amin Karbasi (NeurIPS, 2019)

A New Coding Paradigm for the Primitive Relay Channel. - Marco Mondelli; S. Hamed Hassani; Rüdiger L. Urbanke (Algorithms, 2019)

Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization. - Mingrui Zhang; Lin Chen 003; Aryan Mokhtari; Hamed Hassani; Amin Karbasi (CoRR, 2019)

Stochastic Conditional Gradient++. - Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Zebang Shen (CoRR, 2019)

Construction of Polar Codes With Sublinear Complexity. - Marco Mondelli; S. Hamed Hassani; Rüdiger L. Urbanke (IEEE Trans. Inf. Theory, 2019)

An Exact Quantized Decentralized Gradient Descent Algorithm. - Amirhossein Reisizadeh; Aryan Mokhtari; Hamed Hassani; Ramtin Pedarsani (IEEE Trans. Signal Process., 2019)

Black Box Submodular Maximization: Discrete and Continuous Settings. - Lin Chen 003; Mingrui Zhang; Hamed Hassani; Amin Karbasi (AISTATS, 2020)

FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization. - Amirhossein Reisizadeh; Aryan Mokhtari; Hamed Hassani; Ali Jadbabaie; Ramtin Pedarsani (AISTATS, 2020)

Quantized Frank-Wolfe: Faster Optimization, Lower Communication, and Projection Free. - Mingrui Zhang; Lin Chen 003; Aryan Mokhtari; Hamed Hassani; Amin Karbasi (AISTATS, 2020)

One Sample Stochastic Frank-Wolfe. - Mingrui Zhang; Zebang Shen; Aryan Mokhtari; Hamed Hassani; Amin Karbasi (AISTATS, 2020)

Precise Tradeoffs in Adversarial Training for Linear Regression. - Adel Javanmard; Mahdi Soltanolkotabi; Hamed Hassani (COLT, 2020)

Quantized Decentralized Stochastic Learning over Directed Graphs. - Hossein Taheri; Aryan Mokhtari; Hamed Hassani; Ramtin Pedarsani (ICML, 2020)

Submodular Meta-Learning. - Arman Adibi; Aryan Mokhtari; Hamed Hassani (NeurIPS, 2020)

Sinkhorn Barycenter via Functional Gradient Descent. - Zebang Shen; Zhenfu Wang; Alejandro Ribeiro; Hamed Hassani (NeurIPS, 2020)

Sinkhorn Natural Gradient for Generative Models. - Zebang Shen; Zhenfu Wang; Alejandro Ribeiro; Hamed Hassani (NeurIPS, 2020)

Quantized Push-sum for Gossip and Decentralized Optimization over Directed Graphs. - Hossein Taheri; Aryan Mokhtari; Hamed Hassani; Ramtin Pedarsani (CoRR, 2020)

Model-Based Robust Deep Learning. - Alexander Robey; Hamed Hassani; George J. Pappas (CoRR, 2020)

Learning to Track Dynamic Targets in Partially Known Environments. - Heejin Jeong; Hamed Hassani; Manfred Morari; Daniel D. Lee; George J. Pappas (CoRR, 2020)

Safe Learning under Uncertain Objectives and Constraints. - Mohammad Fereydounian; Zebang Shen; Aryan Mokhtari; Amin Karbasi; Hamed Hassani (CoRR, 2020)

Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization. - Aryan Mokhtari; Hamed Hassani; Amin Karbasi (J. Mach. Learn. Res., 2020)

Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization. - Hamed Hassani; Amin Karbasi; Aryan Mokhtari; Zebang Shen (SIAM J. Optim., 2020)

Online Federated Learning. - Aritra Mitra; Hamed Hassani; George J. Pappas (CDC, 2021)

Federated Learning with Incrementally Aggregated Gradients. - Aritra Mitra; Rayana H. Jaafar; George J. Pappas; Hamed Hassani (CDC, 2021)

Exploiting Shared Representations for Personalized Federated Learning. - Liam Collins; Hamed Hassani; Aryan Mokhtari; Sanjay Shakkottai (ICML, 2021)

Deep Reinforcement Learning for Active Target Tracking. - Heejin Jeong; Hamed Hassani; Manfred Morari; Daniel D. Lee; George J. Pappas (ICRA, 2021)

Optimal Algorithms for Submodular Maximization with Distributed Constraints. - Alexander Robey; Arman Adibi; Brent Schlotfeldt; Hamed Hassani; George J. Pappas (L4DC, 2021)

Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients. - Aritra Mitra; Rayana H. Jaafar; George J. Pappas; Hamed Hassani (NeurIPS, 2021)

Adversarial Robustness with Semi-Infinite Constrained Learning. - Alexander Robey; Luiz F. O. Chamon; George J. Pappas; Hamed Hassani; Alejandro Ribeiro (NeurIPS, 2021)

Model-Based Domain Generalization. - Alexander Robey; George J. Pappas; Hamed Hassani (NeurIPS, 2021)

Achieving Linear Convergence in Federated Learning under Objective and Systems Heterogeneity. - Aritra Mitra; Rayana H. Jaafar; George J. Pappas; Hamed Hassani (CoRR, 2021)

Robust Classification Under 𝓁0 Attack for the Gaussian Mixture Model. - Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (CoRR, 2021)

AutoEKF: Scalable System Identification for COVID-19 Forecasting from Large-Scale GPS Data. - Francisco Barreras; Mikhail Hayhoe; Hamed Hassani; Victor M. Preciado (CoRR, 2021)

Exploiting Heterogeneity in Robust Federated Best-Arm Identification. - Aritra Mitra; Hamed Hassani; George J. Pappas (CoRR, 2021)

Out-of-Distribution Robustness in Deep Learning Compression. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (CoRR, 2021)

Adversarial Tradeoffs in Linear Inverse Problems and Robust State Estimation. - Bruce D. Lee; Thomas T. C. K. Zhang; Hamed Hassani; Nikolai Matni (CoRR, 2021)

Latency-Reliability Tradeoffs for State Estimation. - Konstantinos Gatsis; Hamed Hassani; George J. Pappas (IEEE Trans. Autom. Control., 2021)

Binary Linear Codes With Optimal Scaling: Polar Codes With Large Kernels. - Arman Fazeli; Hamed Hassani; Marco Mondelli; Alexander Vardy (IEEE Trans. Inf. Theory, 2021)

Dynamic Online Learning via Frank-Wolfe Algorithm. - Deepak S. Kalhan; Amrit Singh Bedi; Alec Koppel; Ketan Rajawat; Hamed Hassani; Abhishek K. Gupta; Adrish Banerjee (IEEE Trans. Signal Process., 2021)

Minimax Optimization: The Case of Convex-Submodular. - Arman Adibi; Aryan Mokhtari; Hamed Hassani (AISTATS, 2022)

Federated Functional Gradient Boosting. - Zebang Shen; Hamed Hassani; Satyen Kale; Amin Karbasi (AISTATS, 2022)

Distributed Statistical Min-Max Learning in the Presence of Byzantine Agents. - Arman Adibi; Aritra Mitra; George J. Pappas; Hamed Hassani (CDC, 2022)

Performance-Robustness Tradeoffs in Adversarially Robust Linear-Quadratic Control. - Bruce D. Lee; Thomas T. C. K. Zhang; Hamed Hassani; Nikolai Matni (CDC, 2022)

Chordal Sparsity for Lipschitz Constant Estimation of Deep Neural Networks. - Anton Xue; Lars Lindemann; Alexander Robey; Hamed Hassani; George J. Pappas; Rajeev Alur (CDC, 2022)

Self-Consistency of the Fokker Planck Equation. - Zebang Shen; Zhenfu Wang; Satyen Kale; Alejandro Ribeiro; Amin Karbasi; Hamed Hassani (COLT, 2022)

Adaptive Node Participation for Straggler-Resilient Federated Learning. - Amirhossein Reisizadeh; Isidoros Tziotis; Hamed Hassani; Aryan Mokhtari; Ramtin Pedarsani (ICASSP, 2022)

Low-Complexity Decoding of a Class of Reed-Muller Subcodes for Low-Capacity Channels. - Mohammad Vahid Jamali; Mohammad Fereydounian; Hessam Mahdavifar; Hamed Hassani (ICC, 2022)

An Agnostic Approach to Federated Learning with Class Imbalance. - Zebang Shen; Juan Cerviño; Hamed Hassani; Alejandro Ribeiro (ICLR, 2022)

Do deep networks transfer invariances across classes? - Allan Zhou; Fahim Tajwar; Alexander Robey; Tom Knowles; George J. Pappas; Hamed Hassani; Chelsea Finn (ICLR, 2022)

Probabilistically Robust Learning: Balancing Average and Worst-case Performance. - Alexander Robey; Luiz F. O. Chamon; George J. Pappas; Hamed Hassani (ICML, 2022)

Neural Estimation of the Rate-Distortion Function for Massive Datasets. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (ISIT, 2022)

FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. - Liam Collins; Hamed Hassani; Aryan Mokhtari; Sanjay Shakkottai (NeurIPS, 2022)

Probable Domain Generalization via Quantile Risk Minimization. - Cian Eastwood; Alexander Robey; Shashank Singh 011; Julius von Kügelgen; Hamed Hassani; George J. Pappas; Bernhard Schölkopf (NeurIPS, 2022)

Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints. - Xinmeng Huang; Donghwan Lee; Edgar Dobriban; Hamed Hassani (NeurIPS, 2022)

Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. - Aritra Mitra; Arman Adibi; George J. Pappas; Hamed Hassani (NeurIPS, 2022)

The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression. - Hamed Hassani; Adel Javanmard (CoRR, 2022)

The Exact Class of Graph Functions Generated by Graph Neural Networks. - Mohammad Fereydounian; Hamed Hassani; Javid Dadashkarimi; Amin Karbasi (CoRR, 2022)

Binary Classification Under 𝓁0 Attacks for General Noise Distribution. - Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (CoRR, 2022)

Collaborative Learning of Distributions under Heterogeneity and Communication Constraints. - Xinmeng Huang; Donghwan Lee; Edgar Dobriban; Hamed Hassani (CoRR, 2022)

Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. - Alexander Shevchenko; Kevin Kögler; Hamed Hassani; Marco Mondelli (CoRR, 2022)

Straggler-Resilient Federated Learning: Leveraging the Interplay Between Statistical Accuracy and System Heterogeneity. - Amirhossein Reisizadeh; Isidoros Tziotis; Hamed Hassani; Aryan Mokhtari; Ramtin Pedarsani (IEEE J. Sel. Areas Inf. Theory, 2022)

Robust Classification Under $ ell_0$ Attack for the Gaussian Mixture Model. - Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (SIAM J. Math. Data Sci., 2022)

Age of Information in Random Access Channels. - Xingran Chen; Konstantinos Gatsis; Hamed Hassani; Shirin Saeedi Bidokhti (IEEE Trans. Inf. Theory, 2022)

Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (IEEE J. Sel. Areas Inf. Theory, 2022)

Adversarial Tradeoffs in Robust State Estimation. - Thomas T. C. K. Zhang; Bruce D. Lee; Hamed Hassani; Nikolai Matni (ACC, 2023)

On a Relation Between the Rate-Distortion Function and Optimal Transport. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (Tiny Papers @ ICLR, 2023)

Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning. - Zebang Shen; Jiayuan Ye 001; Anmin Kang; Hamed Hassani; Reza Shokri (ICLR, 2023)

Demystifying Disagreement-on-the-Line in High Dimensions. - Donghwan Lee; Behrad Moniri; Xinmeng Huang; Edgar Dobriban; Hamed Hassani (ICML, 2023)

Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods. - Aleksandr Shevchenko; Kevin Kögler; Hamed Hassani; Marco Mondelli (ICML, 2023)

Federated Neural Compression Under Heterogeneous Data. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (ISIT, 2023)

Generalization Properties of Adversarial Training for -ℓ0 Bounded Adversarial Attacks. - Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (ITW, 2023)

Linear Stochastic Bandits over a Bit-Constrained Channel. - Aritra Mitra; Hamed Hassani; George J. Pappas (L4DC, 2023)

Toward Certified Robustness Against Real-World Distribution Shifts. - Haoze Wu 001; Teruhiro Tagomori; Alexander Robey; Fengjun Yang; Nikolai Matni; George J. Pappas; Hamed Hassani; Corina S. Pasareanu; Clark W. Barrett (SaTML, 2023)

Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity. - Han Wang 016; Aritra Mitra; Hamed Hassani; George J. Pappas; James Anderson 001 (CoRR, 2023)

Optimal Heterogeneous Collaborative Linear Regression and Contextual Bandits. - Xinmeng Huang; Kan Xu; Donghwan Lee; Hamed Hassani; Hamsa Bastani; Edgar Dobriban (CoRR, 2023)

Text + Sketch: Image Compression at Ultra Low Rates. - Eric Lei; Yigit Berkay Uslu; Hamed Hassani; Shirin Saeedi Bidokhti (CoRR, 2023)

Score-Based Methods for Discrete Optimization in Deep Learning. - Eric Lei; Arman Adibi; Hamed Hassani (CoRR, 2023)

Data-Driven Modeling and Verification of Perception-Based Autonomous Systems. - Thomas Waite; Alexander Robey; Hamed Hassani; George J. Pappas; Radoslav Ivanov (CoRR, 2023)

T-Cal: An Optimal Test for the Calibration of Predictive Models. - Donghwan Lee; Xinmeng Huang; Hamed Hassani; Edgar Dobriban (J. Mach. Learn. Res., 2023)

Channel Coding at Low Capacity. - Mohammad Fereydounian; Hamed Hassani; Mohammad Vahid Jamali; Hessam Mahdavifar (IEEE J. Sel. Areas Inf. Theory, 2023)

Straggler-Resilient Personalized Federated Learning. - Isidoros Tziotis; Zebang Shen; Ramtin Pedarsani; Hamed Hassani; Aryan Mokhtari (Trans. Mach. Learn. Res., 2023)

Provably Private Distributed Averaging Consensus: An Information-Theoretic Approach. - Mohammad Fereydounian; Aryan Mokhtari; Ramtin Pedarsani; Hamed Hassani (IEEE Trans. Inf. Theory, 2023)

Provable Tradeoffs in Adversarially Robust Classification. - Edgar Dobriban; Hamed Hassani; David Hong; Alexander Robey (IEEE Trans. Inf. Theory, 2023)

Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. - Arman Adibi; Nicolò Dal Fabbro; Luca Schenato 001; Sanjeev R. Kulkarni; H. Vincent Poor; George J. Pappas; Hamed Hassani; Aritra Mitra (AISTATS, 2024)

Min-Max Optimization Under Delays. - Arman Adibi; Aritra Mitra; Hamed Hassani (ACC, 2024)

Uncertainty in Language Models: Assessment through Rank-Calibration. - Xinmeng Huang; Shuo Li; Mengxin Yu; Matteo Sesia; Hamed Hassani; Insup Lee 001; Osbert Bastani; Edgar Dobriban (EMNLP, 2024)

Adversarial Training Should Be Cast as a Non-Zero-Sum Game. - Alexander Robey; Fabian Latorre; George J. Pappas; Hamed Hassani; Volkan Cevher (ICLR, 2024)

Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks. - Liam Collins; Hamed Hassani; Mahdi Soltanolkotabi; Aryan Mokhtari; Sanjay Shakkottai (ICML, 2024)

Conformal Prediction with Learned Features. - Shayan Kiyani; George J. Pappas; Hamed Hassani (ICML, 2024)

Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. - Kevin Kögler; Aleksandr Shevchenko; Hamed Hassani; Marco Mondelli (ICML, 2024)

A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks. - Behrad Moniri; Donghwan Lee; Hamed Hassani; Edgar Dobriban (ICML, 2024)

JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. - 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 001 (NeurIPS, 2024)

One-Shot Safety Alignment for Large Language Models via Optimal Dualization. - Xinmeng Huang; Shuo Li; Edgar Dobriban; Osbert Bastani; Hamed Hassani; Dongsheng Ding (NeurIPS, 2024)

Length Optimization in Conformal Prediction. - Shayan Kiyani; George J. Pappas; Hamed Hassani (NeurIPS, 2024)

Generalization Properties of Adversarial Training for 𝓁0-Bounded Adversarial Attacks. - Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (CoRR, 2024)

Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth. - Kevin Kögler; Alexander Shevchenko; Hamed Hassani; Marco Mondelli (CoRR, 2024)

Defending Large Language Models against Jailbreak Attacks via Semantic Smoothing. - Jiabao Ji; Bairu Hou; Alexander Robey; George J. Pappas; Hamed Hassani; Yang Zhang 001; Eric Wong 001; Shiyu Chang (CoRR, 2024)

Signal-Plus-Noise Decomposition of Nonlinear Spiked Random Matrix Models. - Behrad Moniri; Hamed Hassani (CoRR, 2024)

Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks. - Mahdi Sabbaghi; George J. Pappas; Hamed Hassani; Surbhi Goel (CoRR, 2024)

Watermarking Language Models with Error Correcting Codes. - Patrick Chao; Edgar Dobriban; Hamed Hassani (CoRR, 2024)

Watermark Smoothing Attacks against Language Models. - Hongyan Chang; Hamed Hassani; Reza Shokri (CoRR, 2024)

Jailbreaking LLM-Controlled Robots. - Alexander Robey; Zachary Ravichandran; Vijay Kumar 001; Hamed Hassani; George J. Pappas (CoRR, 2024)

Conformal Risk Minimization with Variance Reduction. - Sima Noorani; Orlando Romero; Nicolò Dal Fabbro; Hamed Hassani; George J. Pappas (CoRR, 2024)

Efficient and Robust Classification for Sparse Attacks. - Mark Beliaev; Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (IEEE J. Sel. Areas Inf. Theory, 2024)

Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity. - Han Wang 016; Aritra Mitra; Hamed Hassani; George J. Pappas; James Anderson 001 (Trans. Mach. Learn. Res., 2024)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning. - Aritra Mitra; George J. Pappas; Hamed Hassani (Trans. Mach. Learn. Res., 2024)

Binary Classification Under ℓ0 Attacks for General Noise Distribution. - Payam Delgosha; Hamed Hassani; Ramtin Pedarsani (IEEE Trans. Inf. Theory, 2024)

Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (ICLR, 2025)

Asymptotics of Linear Regression with Linearly Dependent Data. - Behrad Moniri; Hamed Hassani (L4DC, 2025)

Evaluating the Performance of Large Language Models via Debates. - Behrad Moniri; Hamed Hassani; Edgar Dobriban (NAACL (Findings), 2025)

Jailbreaking Black Box Large Language Models in Twenty Queries. - Patrick Chao; Alexander Robey; Edgar Dobriban; Hamed Hassani; George J. Pappas; Eric Wong 001 (SaTML, 2025)

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. - Yutong He; Alexander Robey; Naoki Murata; Yiding Jiang; Joshua Nathaniel Williams; George J. Pappas; Hamed Hassani; Yuki Mitsufuji; Ruslan Salakhutdinov; J. Zico Kolter (Trans. Mach. Learn. Res., 2025)

SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks. - Alexander Robey; Eric Wong 001; Hamed Hassani; George J. Pappas (Trans. Mach. Learn. Res., 2025)

Adversarial Reasoning at Jailbreaking Time. - Mahdi Sabbaghi; Paul Kassianik; George J. Pappas; Yaron Singer; Amin Karbasi; Hamed Hassani (CoRR, 2025)

On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning. - Thomas T. Zhang; Behrad Moniri; Ansh Nagwekar; Faraz Rahman; Anton Xue; Hamed Hassani; Nikolai Matni (CoRR, 2025)

Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents. - Shayan Kiyani; George J. Pappas; Aaron Roth 001; Hamed Hassani (CoRR, 2025)

Likelihood-Ratio Regularized Quantile Regression: Adapting Conformal Prediction to High-Dimensional Covariate Shifts. - Sunay Joshi; Shayan Kiyani; George J. Pappas; Edgar Dobriban; Hamed Hassani (CoRR, 2025)

Adaptively evaluating models with task elicitation. - Davis Brown; Prithvi Balehannina; Helen Jin; Shreya Havaldar; Hamed Hassani; Eric Wong 001 (CoRR, 2025)

Safety Guardrails for LLM-Enabled Robots. - Zachary Ravichandran; Alexander Robey; Vijay Kumar 001; George J. Pappas; Hamed Hassani (CoRR, 2025)

Optimal Neural Compressors for the Rate-Distortion-Perception Tradeoff. - Eric Lei; Hamed Hassani; Shirin Saeedi Bidokhti (CoRR, 2025)

On the Mechanisms of Weak-to-Strong Generalization: A Theoretical Perspective. - Behrad Moniri; Hamed Hassani (CoRR, 2025)

Performance-Robustness Tradeoffs in Adversarially Robust Control and Estimation. - Bruce D. Lee; Thomas T. C. K. Zhang; Hamed Hassani; Nikolai Matni (IEEE Trans. Autom. Control., 2025)

Adversarial Attacks on Robotic Vision Language Action Models. - Eliot Krzysztof Jones; Alexander Robey; Andy Zou; Zachary Ravichandran; George J. Pappas; Hamed Hassani; Matt Fredrikson; J. Zico Kolter (CoRR, 2025)

Conformal Prediction Beyond the Seen: A Missing Mass Perspective for Uncertainty Quantification in Generative Models. - Sima Noorani; Shayan Kiyani; George J. Pappas; Hamed Hassani (CoRR, 2025)

Benchmarking Misuse Mitigation Against Covert Adversaries. - Davis Brown; Mahdi Sabbaghi; Luze Sun; Alexander Robey; George J. Pappas; Eric Wong 001; Hamed Hassani (CoRR, 2025)

Conformal Information Pursuit for Interactively Guiding Large Language Models. - Kwan Ho Ryan Chan; Yuyan Ge; Edgar Dobriban; Hamed Hassani; René Vidal (CoRR, 2025)