Sparse linear regression via generalized orthogonal least-squares. - Abolfazl Hashemi; Haris Vikalo (GlobalSIP, 2016)

Sampling Requirements and Accelerated Schemes for Sparse Linear Regression with Orthogonal Least-Squares. - Abolfazl Hashemi; Haris Vikalo (CoRR, 2016)

Sparse recovery via Orthogonal Least-Squares under presence of Noise. - Abolfazl Hashemi; Haris Vikalo (CoRR, 2016)

Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids. - Abolfazl Hashemi; Banghua Zhu; Haris Vikalo (BCB, 2017)

Recovery of sparse signals via Branch and Bound Least-Squares. - Abolfazl Hashemi; Haris Vikalo (ICASSP, 2017)

Accelerated Sparse Subspace Clustering. - Abolfazl Hashemi; Haris Vikalo (CoRR, 2017)

A Randomized Greedy Algorithm for Near-Optimal Sensor Scheduling in Large-Scale Sensor Networks. - Abolfazl Hashemi; Mahsa Ghasemi; Haris Vikalo; Ufuk Topcu (ACC, 2018)

Near-Optimal Distributed Estimation for a Network of Sensing Units Operating Under Communication Constraints. - Abolfazl Hashemi; Osman Fatih Kiliç; Haris Vikalo (CDC, 2018)

A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals. - Abolfazl Hashemi; Rasoul Shafipour; Haris Vikalo; Gonzalo Mateos (GlobalSIP, 2018)

Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation. - Abolfazl Hashemi; Rasoul Shafipour; Haris Vikalo; Gonzalo Mateos (ICASSP, 2018)

Accelerated orthogonal least-squares for large-scale sparse reconstruction. - Abolfazl Hashemi; Haris Vikalo (Digit. Signal Process., 2018)

Evolutionary Self-Expressive Models for Subspace Clustering. - Abolfazl Hashemi; Haris Vikalo (IEEE J. Sel. Top. Signal Process., 2018)

On Submodularity of Quadratic Observation Selection in Constrained Networked Sensing Systems. - Mahsa Ghasemi; Abolfazl Hashemi; Ufuk Topcu; Haris Vikalo (ACC, 2019)

Online Topology Inference from Streaming Stationary Graph Signals. - Rasoul Shafipour; Abolfazl Hashemi; Gonzalo Mateos; Haris Vikalo (DSW, 2019)

A Map Framework for Support Recovery of Sparse Signals Using Orthogonal Least Squares. - Shorya Consul; Abolfazl Hashemi; Haris Vikalo (ICASSP, 2019)

Evolutionary Subspace Clustering: Discovering Structure in Self-expressive Time-series Data. - Abolfazl Hashemi; Haris Vikalo (ICASSP, 2019)

Submodular Observation Selection and Information Gathering for Quadratic Models. - Abolfazl Hashemi; Mahsa Ghasemi; Haris Vikalo; Ufuk Topcu (ICML, 2019)

Stochastic-Greedy++: Closing the Optimality Gap in Exact Weak Submodular Maximization. - Gustavo de Veciana; Abolfazl Hashemi; Haris Vikalo (CoRR, 2019)

Identifying Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach. - Mahsa Ghasemi; Abolfazl Hashemi; Haris Vikalo; Ufuk Topcu (CoRR, 2019)

Identifying Sparse Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach. - Mahsa Ghasemi; Abolfazl Hashemi; Haris Vikalo; Ufuk Topcu (ACC, 2020)

Communication-Efficient Algorithms for Decentralized Optimization Over Directed Graphs. - Yiyue Chen; Abolfazl Hashemi; Haris Vikalo (CoRR, 2020)

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization. - Abolfazl Hashemi; Anish Acharya; Rudrajit Das; Haris Vikalo; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2020)

Improved Convergence Rates for Non-Convex Federated Learning with Compression. - Rudrajit Das; Abolfazl Hashemi; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2020)

Online Learning with Implicit Exploration in Episodic Markov Decision Processes. - Mahsa Ghasemi; Abolfazl Hashemi; Haris Vikalo; Ufuk Topcu (ACC, 2021)

Decentralized Optimization on Time-Varying Directed Graphs Under Communication Constraints. - Yiyue Chen; Abolfazl Hashemi; Haris Vikalo (ICASSP, 2021)

On the Performance-Complexity Tradeoff in Stochastic Greedy Weak Submodular Optimization. - Abolfazl Hashemi; Haris Vikalo; Gustavo de Veciana (ICASSP, 2021)

Physical-Layer Security via Distributed Beamforming in the Presence of Adversaries with Unknown Locations. - Yagiz Savas; Abolfazl Hashemi; Abraham P. Vinod; Brian M. Sadler; Ufuk Topcu (ICASSP, 2021)

No-regret learning with high-probability in adversarial Markov decision processes. - Mahsa Ghasemi; Abolfazl Hashemi; Haris Vikalo; Ufuk Topcu (UAI, 2021)

Function Approximation via Sparse Random Features. - Abolfazl Hashemi; Hayden Schaeffer; Robert Shi; Ufuk Topcu; Giang Tran; Rachel A. Ward (CoRR, 2021)

DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning. - Rudrajit Das; Abolfazl Hashemi; Sujay Sanghavi; Inderjit S. Dhillon (CoRR, 2021)

Robust Generative Adversarial Imitation Learning via Local Lipschitzness. - Farzan Memarian; Abolfazl Hashemi; Scott Niekum; Ufuk Topcu (CoRR, 2021)

Randomized Greedy Sensor Selection: Leveraging Weak Submodularity. - Abolfazl Hashemi; Mahsa Ghasemi; Haris Vikalo; Ufuk Topcu (IEEE Trans. Autom. Control., 2021)

Robust Training in High Dimensions via Block Coordinate Geometric Median Descent. - Anish Acharya; Abolfazl Hashemi; Prateek Jain 002; Sujay Sanghavi; Inderjit S. Dhillon; Ufuk Topcu (AISTATS, 2022)

Faster non-convex federated learning via global and local momentum. - Rudrajit Das; Anish Acharya; Abolfazl Hashemi; Sujay Sanghavi; Inderjit S. Dhillon; Ufuk Topcu (UAI, 2022)

Towards accelerated greedy sampling and reconstruction of bandlimited graph signals. - Abolfazl Hashemi; Rasoul Shafipour; Haris Vikalo; Gonzalo Mateos (Signal Process., 2022)

Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization Over Time-Varying Directed Graphs. - Yiyue Chen; Abolfazl Hashemi; Haris Vikalo (IEEE Trans. Autom. Control., 2022)

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. - Abolfazl Hashemi; Anish Acharya; Rudrajit Das; Haris Vikalo; Sujay Sanghavi; Inderjit S. Dhillon (IEEE Trans. Parallel Distributed Syst., 2022)

On the Benefits of Progressively Increasing Sampling Sizes in Stochastic Greedy Weak Submodular Maximization. - Abolfazl Hashemi; Haris Vikalo; Gustavo de Veciana (IEEE Trans. Signal Process., 2022)

Predictive Estimation for Reinforcement Learning with Time-Varying Reward Functions. - Abolfazl Hashemi; Antesh Upadhyay (ACSSC, 2023)

High Probability Guarantees for Submodular Maximization via Boosted Stochastic Greedy. - Andrés C. Castillo J.; Ege C. Kaya; Abolfazl Hashemi (ACSSC, 2023)

Noisy Communication of Information in Federated Learning: An Improved Convergence Analysis. - Antesh Upadhyay; Abolfazl Hashemi (ACSSC, 2023)

Relative Entropy Regularization for Robust Submodular Multi-Task Subset Selection. - Ege C. Kaya; Abolfazl Hashemi (Allerton, 2023)

High Probability Guarantees For Federated Learning. - Sravani Ramishetty; Abolfazl Hashemi (Allerton, 2023)

Randomized Greedy Algorithms for Sensor Selection in Large-Scale Satellite Constellations. - Michael Hibbard; Abolfazl Hashemi; Takashi Tanaka; Ufuk Topcu (ACC, 2023)

Accelerated Distributed Stochastic Non-Convex Optimization over Time-Varying Directed Networks. - Yiyue Chen; Abolfazl Hashemi; Haris Vikalo (ICASSP, 2023)

Communication-Constrained Exchange of Zeroth-Order Information with Application to Collaborative Target Tracking. - Ege C. Kaya; Mehmet Berk Sahin; Abolfazl Hashemi (ICASSP, 2023)

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data. - Sai Aparna Aketi; Abolfazl Hashemi; Kaushik Roy 001 (NeurIPS, 2023)

Communication-Efficient Zeroth-Order Distributed Online Optimization: Algorithm, Theory, and Applications. - Ege C. Kaya; Mehmet Berk Sahin; Abolfazl Hashemi (IEEE Access, 2023)

Improved Convergence Analysis and SNR Control Strategies for Federated Learning in the Presence of Noise. - Antesh Upadhyay; Abolfazl Hashemi (IEEE Access, 2023)

On the Convergence of Decentralized Federated Learning Under Imperfect Information Sharing. - Vishnu Pandi Chellapandi; Antesh Upadhyay; Abolfazl Hashemi; Stanislaw H. Zak (IEEE Control. Syst. Lett., 2023)

Decentralized Federated Learning: Model Update Tracking Under Imperfect Information Sharing. - Vishnu Pandi Chellapandi; Antesh Upadhyay; Abolfazl Hashemi; Stanislaw H. Zak (IEEE Big Data, 2024)

Equitable Client Selection in Federated Learning via Truncated Submodular Maximization. - Andrés C. Castillo J.; Ege C. Kaya; Lintao Ye; Abolfazl Hashemi (CDC, 2024)

Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression. - Zhankun Luo; Abolfazl Hashemi (ICML, 2024)

Unveiling Privacy, Memorization, and Input Curvature Links. - Deepak Ravikumar; Efstathia Soufleri; Abolfazl Hashemi; Kaushik Roy 001 (ICML, 2024)

Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes. - Sang Bin Moon; Abolfazl Hashemi (UAI, 2024)

FedNMUT - Federated Noisy Model Update Tracking Convergence Analysis. - Vishnu Pandi Chellapandi; Antesh Upadhyay; Abolfazl Hashemi; Stanislaw H. Zak (CoRR, 2024)

AdaGossip: Adaptive Consensus Step-size for Decentralized Deep Learning with Communication Compression. - Sai Aparna Aketi; Abolfazl Hashemi; Kaushik Roy 001 (CoRR, 2024)

Submodular Maximization Approaches for Equitable Client Selection in Federated Learning. - Andrés Catalino Castillo Jiménez; Ege C. Kaya; Lintao Ye; Abolfazl Hashemi (CoRR, 2024)

Equitable Federated Learning with Activation Clustering. - Antesh Upadhyay; Abolfazl Hashemi (CoRR, 2024)

Localized Distributional Robustness in Submodular Multi-Task Subset Selection. - Ege C. Kaya; Abolfazl Hashemi (IEEE Trans. Signal Process., 2024)

No-Regret Learning in Dynamic Stackelberg Games. - Niklas T. Lauffer; Mahsa Ghasemi; Abolfazl Hashemi; Yagiz Savas; Ufuk Topcu (IEEE Trans. Autom. Control., 2024)

Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis. - Guangchen Lan; Dong-Jun Han; Abolfazl Hashemi; Vaneet Aggarwal; Christopher Brinton 001 (ICLR, 2025)

Randomized greedy methods for weak submodular sensor selection with robustness considerations. - Ege C. Kaya; Michael Hibbard; Takashi Tanaka; Ufuk Topcu; Abolfazl Hashemi (Autom., 2025)

An advanced 3D continuum finite element model for field-scale in-situ stress simulation of rock media. - Atefeh Dargahizarandi; Hossein Masoumi; Abolfazl Hashemi; Biswachetan Saha; Hamid Roshan (Simul. Model. Pract. Theory, 2025)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)

Learning to Localize Leakage of Cryptographic Sensitive Variables. - Jimmy Gammell; Anand Raghunathan; Abolfazl Hashemi; Kaushik Roy 001 (CoRR, 2025)

Accelerated Distributed Stochastic Nonconvex Optimization Over Time-Varying Directed Networks. - Yiyue Chen; Abolfazl Hashemi; Haris Vikalo (IEEE Trans. Autom. Control., 2025)

A Unified Model for Large-Scale Inexact Fixed-Point Iteration: A Stochastic Optimization Perspective. - Abolfazl Hashemi (IEEE Trans. Autom. Control., 2025)

Characterizing Evolution in Expectation-Maximization Estimates for Overspecified Mixed Linear Regression. - Zhankun Luo; Abolfazl Hashemi (CoRR, 2025)