Negar Kiyavash

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 144

Top Venues

Publications

Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran
Fast Proxy Experiment Design for Causal Effect Identification. CoRR (2024)
Yuqin Yang, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, AmirEmad Ghassami
Causal Discovery in Linear Models with Unobserved Variables and Measurement Error. CoRR (2024)
Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar, Mathias Drton, Negar Kiyavash
Causal Effect Identification in LiNGAM Models with Latent Confounders. CoRR (2024)
Ehsan Mokhtarian, Sepehr Elahi, Sina Akbari, Negar Kiyavash
Recursive Causal Discovery. CoRR (2024)
Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
Confounded Budgeted Causal Bandits. CLeaR (2024)
Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash
s-ID: Causal Effect Identification in a Sub-population. AAAI (2024)
Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash, Matthias Grossglauser
Causal Effect Identification in a Sub-Population with Latent Variables. CoRR (2024)
Saber Salehkaleybar, Mohammadsadegh Khorasani, Negar Kiyavash, Niao He, Patrick Thiran
Momentum-Based Policy Gradient with Second-Order Information. Trans. Mach. Learn. Res. 2024 (2024)
Yuqin Yang, Saber Salehkaleybar, Negar Kiyavash
Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data. AISTATS (2024)
Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
Confounded Budgeted Causal Bandits. CoRR (2024)
Negar Kiyavash, Elias Bareinboim, Todd P. Coleman, Alex Dimakis, Bernhard Schlkopf, Peter Spirtes, Kun Zhang, Robert Nowak
Editorial Special Issue on Causality: Fundamental Limits and Applications. IEEE J. Sel. Areas Inf. Theory 4 (2023)
Fateme Jamshidi, Luca Ganassali, Negar Kiyavash
On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery. CoRR (2023)
Marc-Aurèle Divernois, Jalal Etesami, Damir Filipovic, Negar Kiyavash
Analysis of Large Market Data Using Neural Networks: A Causal Approach. IEEE J. Sel. Areas Inf. Theory 4 (2023)
Yaroslav Kivva, Jalal Etesami, Negar Kiyavash
On Identifiability of Conditional Causal Effects. CoRR (2023)
Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash
Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. AAAI (2023)
Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash
Causal Effect Identification in Uncertain Causal Networks. NeurIPS (2023)
Sina Akbari, Luca Ganassali, Negar Kiyavash
Learning Causal Graphs via Monotone Triangular Transport Maps. CoRR (2023)
Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash
s-ID: Causal Effect Identification in a Sub-Population. CoRR (2023)
Mikhail Konobeev, Jalal Etesami, Negar Kiyavash
Causal Bandits without Graph Learning. CoRR (2023)
Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian, Siyuan Guo, Yuen Chen, Negar Kiyavash, Mrinmaya Sachan, Bernhard Schölkopf
CausalCite: A Causal Formulation of Paper Citations. CoRR (2023)
Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash
A Cross-Moment Approach for Causal Effect Estimation. CoRR (2023)
Jalal Etesami, Ali Habibnia, Negar Kiyavash
Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework. CoRR (2023)
Yuqin Yang, Saber Salehkaleybar, Negar Kiyavash
Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data. CoRR (2023)
Fateme Jamshidi, Sina Akbari, Negar Kiyavash
Causal Imitability Under Context-Specific Independence Relations. NeurIPS (2023)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash
Gaussian Database Alignment and Gaussian Planted Matching. CoRR (2023)
Sadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash, Niao He, Matthias Grossglauser
Efficiently Escaping Saddle Points for Non-Convex Policy Optimization. CoRR (2023)
Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash
A Cross-Moment Approach for Causal Effect Estimation. NeurIPS (2023)
Fateme Jamshidi, Sina Akbari, Negar Kiyavash
Causal Imitability Under Context-Specific Independence Relations. CoRR (2023)
Yaroslav Kivva, Jalal Etesami, Negar Kiyavash
On Identifiability of Conditional Causal Effects. UAI (2023)
Sina Akbari, Jalal Etesami, Negar Kiyavash
Minimum Cost Intervention Design for Causal Effect Identification. ICML (2022)
Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. CoRR (2022)
Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models. CoRR (2022)
Saber Salehkaleybar, Sadegh Khorasani, Negar Kiyavash, Niao He, Patrick Thiran
Adaptive Momentum-Based Policy Gradient with Second-Order Information. CoRR (2022)
Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. NeurIPS (2022)
Saeed Masiha, Saber Salehkaleybar, Niao He, Negar Kiyavash, Patrick Thiran
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions. NeurIPS (2022)
Saeed Masiha, Saber Salehkaleybar, Niao He, Negar Kiyavash, Patrick Thiran
Stochastic Second-Order Methods Provably Beat SGD For Gradient-Dominated Functions. CoRR (2022)
Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash
Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect. CoRR (2022)
Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash
Revisiting the general identifiability problem. UAI (2022)
Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash
Revisiting the General Identifiability Problem. CoRR (2022)
Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
Causal Effect Identification with Context-specific Independence Relations of Control Variables. AISTATS (2022)
Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
Learning Bayesian Networks in the Presence of Structural Side Information. AAAI (2022)
Sina Akbari, Jalal Etesami, Negar Kiyavash
Minimum Cost Intervention Design for Causal Effect Identification. CoRR (2022)
Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash
Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. CoRR (2022)
Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CLeaR (2022)
Ilyas Fatkhullin, Jalal Etesami, Niao He, Negar Kiyavash
Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality. NeurIPS (2022)
Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
Learning Bayesian Networks in the Presence of Structural Side Information. CoRR (2021)
Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran
A Variational Inference Approach to Learning Multivariate Wold Processes. AISTATS (2021)
Thuc Duy Le, Jiuyong Li, Gregory Cooper, Sofia Triantafillou, Elias Bareinboim, Huan Liu, Negar Kiyavash
The KDD 2021 Workshop on Causal Discovery (CD2021). KDD (2021)
William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran
Cumulants of Hawkes Processes are Robust to Observation Noise. ICML (2021)
Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. NeurIPS (2021)
Yuqin Yang, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
Causal Discovery in Linear Structural Causal Models with Deterministic Relations. CoRR (2021)
S. Rasoul Etesami, Negar Kiyavash, Vincent Léon, H. Vincent Poor
Optimal Adversarial Policies in the Multiplicative Learning System With a Malicious Expert. IEEE Trans. Inf. Forensics Secur. 16 (2021)
Anshul Gandhi, Negar Kiyavash, Jia Wang
Editorial. Proc. ACM Meas. Anal. Comput. Syst. 5 (2) (2021)
Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash
A Recursive Markov Boundary-Based Approach to Causal Structure Learning. CD@KDD (2021)
Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
Impact of Data Processing on Fairness in Supervised Learning. ISIT (2021)
Sina Akbari, Ehsan Mokhtarian, AmirEmad Ghassami, Negar Kiyavash
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias. CoRR (2021)
Sajad Khodadadian, Mohamed S. Nafea, AmirEmad Ghassami, Negar Kiyavash
Information Theoretic Measures for Fairness-aware Feature Selection. CoRR (2021)
Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization. CoRR (2021)
Sajad Khodadadian, AmirEmad Ghassami, Negar Kiyavash
Impact of Data Processing on Fairness in Supervised Learning. CoRR (2021)
Anh Truong, S. Rasoul Etesami, Negar Kiyavash
Selective Labeling in Learning with Expert Advice. ACC (2021)
Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He
The complexity of nonconvex-strongly-concave minimax optimization. UAI (2021)
Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
Causal Effect Identification with Context-specific Independence Relations of Control Variables. CoRR (2021)
Thuc Duy Le, Jiuyong Li, Gregory Cooper, Sofia Triantafyllou, Elias Bareinboim, Huan Liu, Negar Kiyavash
Preface: The 2021 ACM SIGKDD Workshop on Causal Discovery. CD@KDD (2021)
Junchi Yang, Negar Kiyavash, Niao He
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems. CoRR (2020)
Daniel Cullina, Negar Kiyavash, Prateek Mittal, H. Vincent Poor
Partial Recovery of Erdős-Rényi Graph Alignment via k-Core Alignment. SIGMETRICS (Abstracts) (2020)
Ehsan Mokhtarian, Sina Akbari, AmirEmad Ghassami, Negar Kiyavash
A Recursive Markov Blanket-Based Approach to Causal Structure Learning. CoRR (2020)
Junchi Yang, Siqi Zhang, Negar Kiyavash, Niao He
A Catalyst Framework for Minimax Optimization. NeurIPS (2020)
Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum
Model-Augmented Conditional Mutual Information Estimation for Feature Selection. UAI (2020)
Ali AhmadiTeshnizi, Saber Salehkaleybar, Negar Kiyavash
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments. CoRR (2020)
Antonio G. Marques, Negar Kiyavash, José M. F. Moura, Dimitri Van De Ville, Rebecca Willett
Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]. IEEE Signal Process. Mag. 37 (6) (2020)
Junchi Yang, Negar Kiyavash, Niao He
Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax Problems. NeurIPS (2020)
Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. J. Mach. Learn. Res. 21 (2020)
Ali AhmadiTeshnizi, Saber Salehkaleybar, Negar Kiyavash
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments. ICML (2020)
Yingxiang Yang, Negar Kiyavash, Le Song, Niao He
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models. NeurIPS (2020)
Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash
Achievability of nearly-exact alignment for correlated Gaussian databases. ISIT (2020)
S. Rasoul Etesami, Negar Kiyavash, H. Vincent Poor
Adversarial Policies in Learning Systems with Malicious Experts. CoRR (2020)
AmirEmad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs. ICML (2020)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash
Database Alignment with Gaussian Features. CoRR (2019)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
Interventional Experiment Design for Causal Structure Learning. CoRR (2019)
Chien-Ying Chen, Sibin Mohan, Rodolfo Pellizzoni, Rakesh B. Bobba, Negar Kiyavash
A Novel Side-Channel in Real-Time Schedulers. RTAS (2019)
Ge Yu, Sheldon H. Jacobson, Negar Kiyavash
A bi-criteria multiple-choice secretary problem. IISE Trans. 51 (6) (2019)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash, Matthias Grossglauser
Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdos-Rényi Graphs. Proc. ACM Meas. Anal. Comput. Syst. 3 (2) (2019)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash, Matthias Grossglauser
Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdős-Rényi Graphs. SIGMETRICS (Abstracts) (2019)
Alan Yang, AmirEmad Ghassami, Maxim Raginsky, Negar Kiyavash, Elyse Rosenbaum
Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection. CoRR (2019)
Saber Salehkaleybar, AmirEmad Ghassami, Negar Kiyavash, Kun Zhang
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. CoRR (2019)
Yingxiang Yang, Haoxiang Wang, Negar Kiyavash, Niao He
Learning Positive Functions with Pseudo Mirror Descent. NeurIPS (2019)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees. AAAI (2019)
Daniel Cullina, Negar Kiyavash, Prateek Mittal, H. Vincent Poor
Partial Recovery of Erdðs-Rényi Graph Alignment via k-Core Alignment. Proc. ACM Meas. Anal. Comput. Syst. 3 (3) (2019)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash
Database Alignment with Gaussian Features. AISTATS (2019)
AmirEmad Ghassami, Kun Zhang, Negar Kiyavash
Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs. CoRR (2019)
William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran
Learning Hawkes Processes Under Synchronization Noise. ICML (2019)
Daniel Cullina, Prateek Mittal, Negar Kiyavash
Fundamental Limits of Database Alignment. ISIT (2018)
Osman Emre Dai, Daniel Cullina, Negar Kiyavash, Matthias Grossglauser
On the Performance of a Canonical Labeling for Matching Correlated Erdős-Rényi Graphs. CoRR (2018)
Daniel Cullina, Prateek Mittal, Negar Kiyavash
Fundamental Limits of Database Alignment. CoRR (2018)
Yingxiang Yang, Bo Dai, Negar Kiyavash, Niao He
Predictive Approximate Bayesian Computation via Saddle Points. NeurIPS (2018)
Daniel Cullina, Negar Kiyavash, Prateek Mittal, H. Vincent Poor
Partial Recovery of Erdős-Rényi Graph Alignment via k-Core Alignment. CoRR (2018)
Chien-Ying Chen, Monowar Hasan, AmirEmad Ghassami, Sibin Mohan, Negar Kiyavash
REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation. CoRR (2018)
Chien-Ying Chen, Sibin Mohan, Rakesh B. Bobba, Rodolfo Pellizzoni, Negar Kiyavash
ScheduLeak: A Novel Scheduler Side-Channel Attack Against Real-Time Autonomous Control Systems. CoRR (2018)
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash
Counting and Uniform Sampling from Markov Equivalent DAGs. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Negar Kiyavash