Jalal Etesami

According to our database, Jalal Etesami authored at least 40 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Confounded Budgeted Causal Bandits.

Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

CoRR, 2024

2023

Analysis of Large Market Data Using Neural Networks: A Causal Approach.

Marc-Aurèle Divernois, Jalal Etesami, Damir Filipovic, Negar Kiyavash

IEEE J. Sel. Areas Inf. Theory, 2023

Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework.

Jalal Etesami, Ali Habibnia, Negar Kiyavash

CoRR, 2023

Causal Bandits without Graph Learning.

Mikhail Konobeev, Jalal Etesami, Negar Kiyavash

CoRR, 2023

On Identifiability of Conditional Causal Effects.

Yaroslav Kivva, Jalal Etesami, Negar Kiyavash

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Causal Effect Identification in Uncertain Causal Networks.

Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables.

Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect.

Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash

CoRR, 2022

A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics.

Matthew J. Vowels, Sina Akbari, Jalal Etesami, Necati Cihan Camgöz, Richard Bowden

CoRR, 2022

Revisiting the general identifiability problem.

Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality.

Ilyas Fatkhullin, Jalal Etesami, Niao He, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Minimum Cost Intervention Design for Causal Effect Identification.

Sina Akbari, Jalal Etesami, Negar Kiyavash

Proceedings of the International Conference on Machine Learning, 2022

Causal Effect Identification with Context-specific Independence Relations of Control Variables.

Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Bayesian Networks in the Presence of Structural Side Information.

Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Cumulants of Hawkes Processes are Robust to Observation Noise.

William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran

Proceedings of the 38th International Conference on Machine Learning, 2021

A Variational Inference Approach to Learning Multivariate Wold Processes.

Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Non-cooperative Multi-agent Systems with Exploring Agents.

Jalal Etesami, Christoph-Nikolas Straehle

CoRR, 2020

Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift.

Jalal Etesami, Philipp Geiger

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Wasserstein Adversarial Imitation Learning.

Huang Xiao, Michael Herman, Jörg Wagner, Sebastian Ziesche, Jalal Etesami, Thai Hong Linh

CoRR, 2019

Learning Hawkes Processes Under Synchronization Noise.

William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Optimal Attack Strategies Against Predictors - Learning From Expert Advice.

Anh Truong, S. Rasoul Etesami, Jalal Etesami, Negar Kiyavash

IEEE Trans. Inf. Forensics Secur., 2018

Learning Vector Autoregressive Models With Latent Processes.

Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, Kun Zhang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Measuring Causal Relationships in Dynamical Systems through Recovery of Functional Dependencies.

Jalal Etesami, Negar Kiyavash

IEEE Trans. Signal Inf. Process. over Networks, 2017

Learning Latent Networks in Vector Auto Regressive Models.

Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash

CoRR, 2017

A New Measure of Conditional Dependence for Causal Structural Learning.

Jalal Etesami, Kun Zhang, Negar Kiyavash

CoRR, 2017

Online Learning for Multivariate Hawkes Processes.

Yingxiang Yang, Jalal Etesami, Niao He, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Identifying nonlinear 1-step causal influences in presence of latent variables.

Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Efficient neighborhood selection for walk summable Gaussian graphical models.

Yingxang Yang, Jalal Etesami, Negar Kiyavash

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Learning Minimal Latent Directed Information Polytrees.

Jalal Etesami, Negar Kiyavash, Todd P. Coleman

Neural Comput., 2016

On the Vulnerability of Digital Fingerprinting Systems to Finite Alphabet Collusion Attacks.

Jalal Etesami, Negar Kiyavash

CoRR, 2016

Learning Network of Multivariate Hawkes Processes: A Time Series Approach.

Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Interventional dependency graphs: An approach for discovering influence structure.

Jalal Etesami, Negar Kiyavash

Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

Efficient Neighborhood Selection for Gaussian Graphical Models.

Yingxiang Yang, Jalal Etesami, Negar Kiyavash

CoRR, 2015

2014

A novel collusion attack on finite alphabet digital fingerprinting systems.

Jalal Etesami, Negar Kiyavash

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Directed Information Graphs: A generalization of Linear Dynamical Graphs.

Jalal Etesami, Negar Kiyavash

Proceedings of the American Control Conference, 2014

2013

Robust directed tree approximations for networks of stochastic processes.

Christopher J. Quinn, Jalal Etesami, Negar Kiyavash, Todd P. Coleman

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2012

Learning minimal latent directed information trees.

Jalal Etesami, Negar Kiyavash, Todd P. Coleman

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

LDPC code construction for wireless physical-layer key reconciliation.

Jalal Etesami, Werner Henkel

Proceedings of the 2012 1st IEEE International Conference on Communications in China (ICCC), 2012

2011

Iterative distributed channel probing for cognitive radios with power-controlled wireless links.

Jafar Mohammadi, Slawomir Stanczak, Renato L. G. Cavalcante, Jalal Etesami

Proceedings of the 8th International Symposium on Wireless Communication Systems, 2011

LCD Codes and Iterative Decoding by Projections, a First Step Towards an Intuitive Description of Iterative Decoding.

Jalal Etesami, Fangning Hu, Werner Henkel

Proceedings of the Global Communications Conference, 2011