QoS-aware joint policies in cognitive radio networks. - Saber Salehkaleybar; Seyyed Arash Majd; Mohammad Reza Pakravan (IWCMC, 2011)

Averaging consensus over erasure channels via local synchronization. - Saber Salehkaleybar; S. Jamaloddin Golestani (ISIT, 2013)

Delay analysis and buffer management for random access in cognitive radio networks. - Saber Salehkaleybar; Seyyed Arash Majd; Mohammad Reza Pakravan (IWCIT, 2013)

Distributed Voting/Ranking With Optimal Number of States per Node. - Saber Salehkaleybar; Arsalan Sharif-Nassab; S. Jamaloddin Golestani (IEEE Trans. Signal Inf. Process. over Networks, 2015)

A periodic jump-based rendezvous algorithm in cognitive radio networks. - Saber Salehkaleybar; Mohammad Reza Pakravan (Comput. Commun., 2016)

Distributed binary majority voting via exponential distribution. - Saber Salehkaleybar; Sayyed Jamaloddin Golestani (IET Signal Process., 2016)

Token-Based Function Computation with Memory. - Saber Salehkaleybar; S. Jamaloddin Golestani (IEEE Trans. Parallel Distributed Syst., 2016)

Identifying nonlinear 1-step causal influences in presence of latent variables. - Saber Salehkaleybar; Jalal Etesami; Negar Kiyavash (ISIT, 2017)

Learning Causal Structures Using Regression Invariance. - AmirEmad Ghassami; Saber Salehkaleybar; Negar Kiyavash; Kun Zhang 001 (NIPS, 2017)

Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments. - AmirEmad Ghassami; Saber Salehkaleybar; Negar Kiyavash (CoRR, 2017)

Learning Latent Networks in Vector Auto Regressive Models. - Saber Salehkaleybar; Jalal Etesami; Negar Kiyavash (CoRR, 2017)

Learning Vector Autoregressive Models With Latent Processes. - Saber Salehkaleybar; Jalal Etesami; Negar Kiyavash; Kun Zhang 001 (AAAI, 2018)

Budgeted Experiment Design for Causal Structure Learning. - AmirEmad Ghassami; Saber Salehkaleybar; Negar Kiyavash; Elias Bareinboim (ICML, 2018)

Counting and Uniform Sampling from Markov Equivalent DAGs. - AmirEmad Ghassami; Saber Salehkaleybar; Negar Kiyavash (CoRR, 2018)

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees. - AmirEmad Ghassami; Saber Salehkaleybar; Negar Kiyavash; Kun Zhang 001 (AAAI, 2019)

Order Optimal One-Shot Distributed Learning. - Arsalan Sharif-Nassab; Saber Salehkaleybar; S. Jamaloddin Golestani (NeurIPS, 2019)

Theoretical Limits of One-Shot Distributed Learning. - Saber Salehkaleybar; Arsalan Sharif-Nassab; S. Jamaloddin Golestani (CoRR, 2019)

Seedless Graph Matching via Tail of Degree Distribution for Correlated Erdos-Renyi Graphs. - Mahdi Bozorg; Saber Salehkaleybar; Matin Hashemi (CoRR, 2019)

Interventional Experiment Design for Causal Structure Learning. - AmirEmad Ghassami; Saber Salehkaleybar; Negar Kiyavash (CoRR, 2019)

Bounds on Over-Parameterization for Guaranteed Existence of Descent Paths in Shallow ReLU Networks. - Arsalan Sharif-Nassab; Saber Salehkaleybar; S. Jamaloddin Golestani (ICLR, 2020)

LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments. - Ali AhmadiTeshnizi; Saber Salehkaleybar; Negar Kiyavash (ICML, 2020)

Multi Variable-layer Neural Networks for Decoding Linear Codes. - Samira Malek; Saber Salehkaleybar; Arash Amini (IWCIT, 2020)

GPU Accelerated RIS-based Influence Maximization Algorithm. - Soheil Shahrouz; Saber Salehkaleybar; Matin Hashemi (CoRR, 2020)

Broadcast distributed voting algorithm in population protocols. - Hamidreza Bandealinaeini; Saber Salehkaleybar (IET Signal Process., 2020)

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. - Saber Salehkaleybar; AmirEmad Ghassami; Negar Kiyavash; Kun Zhang 001 (J. Mach. Learn. Res., 2020)

Distributed voting in beep model. - Benyamin Ghojogh; Saber Salehkaleybar (Signal Process., 2020)

cuPC: CUDA-Based Parallel PC Algorithm for Causal Structure Learning on GPU. - Behrooz Zarebavani; Foad Jafarinejad; Matin Hashemi; Saber Salehkaleybar (IEEE Trans. Parallel Distributed Syst., 2020)

Order Optimal One-Shot Federated Learning for non-Convex Loss Functions. - Arsalan Sharif-Nassab; Saber Salehkaleybar; S. Jamaloddin Golestani (CoRR, 2021)

Causal Imitative Model for Autonomous Driving. - Mohammad Reza Samsami; Mohammadhossein Bahari; Saber Salehkaleybar; Alexandre Alahi (CoRR, 2021)

One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them. - Saber Salehkaleybar; Arsalan Sharif-Nassab; S. Jamaloddin Golestani (J. Mach. Learn. Res., 2021)

Adversarial orthogonal regression: Two non-linear regressions for causal inference. - M. Reza Heydari; Saber Salehkaleybar; Kun Zhang 001 (Neural Networks, 2021)

gIM: GPU Accelerated RIS-Based Influence Maximization Algorithm. - Soheil Shahrouz; Saber Salehkaleybar; Matin Hashemi (IEEE Trans. Parallel Distributed Syst., 2021)

Deep-Learning-Based Blind Recognition of Channel Code Parameters Over Candidate Sets Under AWGN and Multi-Path Fading Conditions. - Sepehr Dehdashtian; Matin Hashemi; Saber Salehkaleybar (IEEE Wirel. Commun. Lett., 2021)

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions. - Saeed Masiha; Saber Salehkaleybar; Niao He; Negar Kiyavash; Patrick Thiran (NeurIPS, 2022)

Adaptive Momentum-Based Policy Gradient with Second-Order Information. - Saber Salehkaleybar; Sadegh Khorasani; Negar Kiyavash; Niao He; Patrick Thiran (CoRR, 2022)

Stochastic Second-Order Methods Provably Beat SGD For Gradient-Dominated Functions. - Saeed Masiha; Saber Salehkaleybar; Niao He; Negar Kiyavash; Patrick Thiran (CoRR, 2022)

Active learning of causal structures with deep reinforcement learning. - Amir Amirinezhad; Saber Salehkaleybar; Matin Hashemi (Neural Networks, 2022)

A Cross-Moment Approach for Causal Effect Estimation. - Yaroslav Kivva; Saber Salehkaleybar; Negar Kiyavash (NeurIPS, 2023)

Efficiently Escaping Saddle Points for Non-Convex Policy Optimization. - Sadegh Khorasani; Saber Salehkaleybar; Negar Kiyavash; Niao He; Matthias Grossglauser (CoRR, 2023)

Fast causal orientation learning in directed acyclic graphs. - Ramin Safaeian; Saber Salehkaleybar; Mahmoud Tabandeh (Int. J. Approx. Reason., 2023)

A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. - Ehsan Mokhtarian; Saber Salehkaleybar; AmirEmad Ghassami; Negar Kiyavash (J. Mach. Learn. Res., 2023)

ParaLiNGAM: Parallel causal structure learning for linear non-Gaussian acyclic models. - Amirhossein Shahbazinia; Saber Salehkaleybar; Matin Hashemi (J. Parallel Distributed Comput., 2023)

Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data. - Yuqin Yang; Saber Salehkaleybar; Negar Kiyavash (AISTATS, 2024)

Causal Effect Identification in LiNGAM Models with Latent Confounders. - Daniele Tramontano; Yaroslav Kivva; Saber Salehkaleybar; Mathias Drton; Negar Kiyavash (ICML, 2024)

MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters. - Arsalan Sharifnassab; Saber Salehkaleybar; Richard S. Sutton (CoRR, 2024)

Soft Preference Optimization: Aligning Language Models to Expert Distributions. - Arsalan Sharifnassab; Sina Ghiassian; Saber Salehkaleybar; Surya Kanoria; Dale Schuurmans (CoRR, 2024)

Complexity of Minimizing Projected-Gradient-Dominated Functions with Stochastic First-order Oracles. - Saeed Masiha; Saber Salehkaleybar; Niao He; Negar Kiyavash; Patrick Thiran (CoRR, 2024)

Momentum-Based Policy Gradient with Second-Order Information. - Saber Salehkaleybar; Mohammadsadegh Khorasani; Negar Kiyavash; Niao He; Patrick Thiran (Trans. Mach. Learn. Res., 2024)

Order Optimal Bounds for One-Shot Federated Learning Over Non-Convex Loss Functions. - Arsalan Sharif-Nassab; Saber Salehkaleybar; S. Jamaloddin Golestani (IEEE Trans. Inf. Theory, 2024)

Multi-Domain Causal Discovery in Bijective Causal Models. - Kasra Jalaldoust; Saber Salehkaleybar; Negar Kiyavash (CLeaR, 2025)

Efficiently Escaping Saddle Points for Policy Optimization. - Mohammadsadegh Khorasani; Saber Salehkaleybar; Negar Kiyavash; Niao He; Matthias Grossglauser (UAI, 2025)

Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments. - Yaroslav Kivva; Sina Akbari; Saber Salehkaleybar; Negar Kiyavash (UAI, 2025)

ACTIVA: Amortized Causal Effect Estimation without Graphs via Transformer-based Variational Autoencoder. - Andreas Sauter; Saber Salehkaleybar; Aske Plaat; Erman Acar (CoRR, 2025)

Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants. - Daniele Tramontano; Yaroslav Kivva; Saber Salehkaleybar; Mathias Drton; Negar Kiyavash (CoRR, 2025)

Hierarchical Reinforcement Learning with Targeted Causal Interventions. - Sadegh Khorasani; Saber Salehkaleybar; Negar Kiyavash; Matthias Grossglauser (CoRR, 2025)

Causal Reasoning in Pieces: Modular In-Context Learning for Causal Discovery. - Kacper Kadziolka; Saber Salehkaleybar (CoRR, 2025)

Fusing Rewards and Preferences in Reinforcement Learning. - Sadegh Khorasani; Saber Salehkaleybar; Negar Kiyavash; Matthias Grossglauser (CoRR, 2025)