Kiyavash, Negar

61 publications

CLeaR 2025 Causal Bandits Without Graph Learning Mikhail Konobeev, Jalal Etesami, Negar Kiyavash

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

UAI 2025 Multi-Armed Bandits with Missing Outcomes Ilia Mahrooghi, Mahshad Moradi, Sina Akbari, Negar Kiyavash

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

JMLR 2025 Optimal Experiment Design for Causal Effect Identification Sina Akbari, Jalal Etesami, Negar Kiyavash

JMLR 2025 Recursive Causal Discovery Ehsan Mokhtarian, Sepehr Elahi, Sina Akbari, Negar Kiyavash

CLeaR 2025 Sample Complexity of Nonparametric Closeness Testing for Continuous Distributions and Its Application to Causal Discovery with Hidden Confounding Fateme Jamshidi, Sina Akbari, Negar Kiyavash

NeurIPSW 2024 Causal Discovery in Linear Models with Unobserved Variables and Measurement Error Yuqin Yang, Mohamed S Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami

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

NeurIPS 2024 Causal Effect Identification in a Sub-Population with Latent Variables Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash, Matthias Grossglauser

CLeaR 2024 Confounded Budgeted Causal Bandits Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

NeurIPS 2024 Fast Proxy Experiment Design for Causal Effect Identification Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran

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

ICML 2024 On the Sample Complexity of Conditional Independence Testing with Von Mises Estimator with Application to Causal Discovery Fateme Jamshidi, Luca Ganassali, Negar Kiyavash

UAI 2024 Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence – Preface Negar Kiyavash, Joris M. Mooij

NeurIPS 2024 QWO: Speeding up Permutation-Based Causal Discovery in LiGAMs Mohammad Shahverdikondori, Ehsan Mokhtarian, Negar Kiyavash

AAAI 2024 S-ID: Causal Effect Identification in a Sub-Population Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash

ICML 2024 Triple Changes Estimator for Targeted Policies Sina Akbari, Negar Kiyavash

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 Causal Discovery via Monotone Triangular Transport Maps Sina Akbari, Luca Ganassali, Negar Kiyavash

NeurIPS 2023 Causal Effect Identification in Uncertain Causal Networks Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew Vowels, Jalal Etesami, Negar Kiyavash

NeurIPS 2023 Causal Imitability Under Context-Specific Independence Relations Fateme Jamshidi, Sina Akbari, Negar Kiyavash

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

AAAI 2023 Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash

UAI 2023 On Identifiability of Conditional Causal Effects Yaroslav Kivva, Jalal Etesami, Negar Kiyavash

AISTATS 2022 Causal Effect Identification with Context-Specific Independence Relations of Control Variables Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

NeurIPS 2022 Causal Discovery in Linear Latent Variable Models Subject to Measurement Error Yuqin Yang, AmirEmad Ghassami, Mohamed Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser

CLeaR 2022 Causal Discovery in Linear Structural Causal Models with Deterministic Relations Yuqin Yang, Mohamed S Nafea, AmirEmad Ghassami, Negar Kiyavash

AAAI 2022 Learning Bayesian Networks in the Presence of Structural Side Information Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

ICML 2022 Minimum Cost Intervention Design for Causal Effect Identification Sina Akbari, Jalal Etesami, Negar Kiyavash

UAI 2022 Revisiting the General Identifiability Problem Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash

NeurIPS 2022 Sharp Analysis of Stochastic Optimization Under Global Kurdyka-Lojasiewicz Inequality Ilyas Fatkhullin, Jalal Etesami, Niao He, 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

AISTATS 2021 A Variational Inference Approach to Learning Multivariate Wold Processes Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran

ICML 2021 Cumulants of Hawkes Processes Are Robust to Observation Noise William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran

NeurIPS 2021 Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash

UAI 2021 The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He

NeurIPS 2020 A Catalyst Framework for Minimax Optimization Junchi Yang, Siqi Zhang, Negar Kiyavash, Niao He

ICML 2020 Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs Amiremad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang

NeurIPS 2020 Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems Junchi Yang, Negar Kiyavash, Niao He

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

UAI 2020 Model-Augmented Conditional Mutual Information Estimation for Feature Selection Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum

NeurIPS 2020 The Devil Is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models Yingxiang Yang, Negar Kiyavash, Le Song, Niao He

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

AISTATS 2019 Database Alignment with Gaussian Features Osman E. Dai, Daniel Cullina, Negar Kiyavash

ICML 2019 Learning Hawkes Processes Under Synchronization Noise William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran

NeurIPS 2019 Learning Positive Functions with Pseudo Mirror Descent Yingxiang Yang, Haoxiang Wang, Negar Kiyavash, Niao He

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 2018 Multi-Domain Causal Structure Learning in Linear Systems AmirEmad Ghassami, Negar Kiyavash, Biwei Huang, Kun Zhang

NeurIPS 2018 Predictive Approximate Bayesian Computation via Saddle Points Yingxiang Yang, Bo Dai, Negar Kiyavash, Niao He

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

NeurIPS 2017 Online Learning for Multivariate Hawkes Processes Yingxiang Yang, Jalal Etesami, Niao He, Negar Kiyavash

UAI 2016 Learning Network of Multivariate Hawkes Processes: A Time Series Approach Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal