Salehkaleybar, Saber

23 publications

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

ICML 2025 Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash, Mathias Drton

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

ICML 2025 Hierarchical Reinforcement Learning with Targeted Causal Interventions Mohammadsadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash, Matthias Grossglauser

ICML 2025 MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-Parameters Arsalan Sharifnassab, Saber Salehkaleybar, Richard S. Sutton

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

NeurIPS 2025 Near-Optimal Experiment Design in Linear Non-Gaussian Cyclic Models Ehsan Sharifian, Saber Salehkaleybar, Negar Kiyavash

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

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

TMLR 2024 Momentum-Based Policy Gradient with Second-Order Information Saber Salehkaleybar, Mohammadsadegh Khorasani, Negar Kiyavash, Niao He, Patrick Thiran

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

JMLR 2023 A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash

NeurIPSW 2023 Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data Yuqin Yang, Saber Salehkaleybar, Negar Kiyavash

NeurIPS 2022 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

JMLR 2021 One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them Saber Salehkaleybar, Arsalan Sharifnassab, S. Jamaloddin Golestani

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

ICML 2020 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments Ali Ahmaditeshnizi, Saber Salehkaleybar, Negar Kiyavash

JMLR 2020 Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang

AAAI 2019 Counting and Sampling from Markov Equivalent DAGs Using Clique Trees AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang

NeurIPS 2019 Order Optimal One-Shot Distributed Learning Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani

ICML 2018 Budgeted Experiment Design for Causal Structure Learning AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Elias Bareinboim

AAAI 2018 Learning Vector Autoregressive Models with Latent Processes Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, Kun Zhang

NeurIPS 2017 Learning Causal Structures Using Regression Invariance AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang