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Jalal Etesami
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2020 – today
- 2024
- [c26]Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Confounded Budgeted Causal Bandits. CLeaR 2024: 423-461 - [i21]Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Confounded Budgeted Causal Bandits. CoRR abs/2401.07578 (2024) - [i20]Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran:
Fast Proxy Experiment Design for Causal Effect Identification. CoRR abs/2407.05330 (2024) - 2023
- [j4]Marc-Aurèle Divernois, Jalal Etesami
, Damir Filipovic
Analysis of Large Market Data Using Neural Networks: A Causal Approach. IEEE J. Sel. Areas Inf. Theory 4: 833-847 (2023) - [c25]Ehsan Mokhtarian
Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. AAAI 2023: 12260-12268 - [c24]Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Effect Identification in Uncertain Causal Networks. NeurIPS 2023 - [c23]Yaroslav Kivva, Jalal Etesami, Negar Kiyavash:
On Identifiability of Conditional Causal Effects. UAI 2023: 1078-1086 - [i19]Mikhail Konobeev, Jalal Etesami, Negar Kiyavash:
Causal Bandits without Graph Learning. CoRR abs/2301.11401 (2023) - [i18]Yaroslav Kivva, Jalal Etesami, Negar Kiyavash:
On Identifiability of Conditional Causal Effects. CoRR abs/2306.11755 (2023) - [i17]Jalal Etesami, Ali Habibnia, Negar Kiyavash:
Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework. CoRR abs/2312.16707 (2023) - 2022
- [c22]Ehsan Mokhtarian
Learning Bayesian Networks in the Presence of Structural Side Information. AAAI 2022: 7814-7822 - [c21]Ehsan Mokhtarian
Causal Effect Identification with Context-specific Independence Relations of Control Variables. AISTATS 2022: 11237-11246 - [c20]Sina Akbari, Jalal Etesami, Negar Kiyavash:
Minimum Cost Intervention Design for Causal Effect Identification. ICML 2022: 258-289 - [c19]Ilyas Fatkhullin, Jalal Etesami, Niao He, Negar Kiyavash:
Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality. NeurIPS 2022 - [c18]Yaroslav Kivva, Ehsan Mokhtarian
Revisiting the general identifiability problem. UAI 2022: 1022-1030 - [i16]Matthew J. Vowels, Sina Akbari, Jalal Etesami, Necati Cihan Camgöz, Richard Bowden:
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics. CoRR abs/2202.09096 (2022) - [i15]Sina Akbari, Jalal Etesami, Negar Kiyavash:
Minimum Cost Intervention Design for Causal Effect Identification. CoRR abs/2205.02232 (2022) - [i14]Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash:
Revisiting the General Identifiability Problem. CoRR abs/2206.01081 (2022) - [i13]Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash:
Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect. CoRR abs/2208.04627 (2022) - [i12]Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash:
Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. CoRR abs/2208.06935 (2022) - 2021
- [c17]Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran:
A Variational Inference Approach to Learning Multivariate Wold Processes. AISTATS 2021: 2044-2052 - [c16]William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran:
Cumulants of Hawkes Processes are Robust to Observation Noise. ICML 2021: 10444-10454 - [i11]Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Causal Effect Identification with Context-specific Independence Relations of Control Variables. CoRR abs/2110.12064 (2021) - [i10]Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash:
Learning Bayesian Networks in the Presence of Structural Side Information. CoRR abs/2112.10884 (2021) - 2020
- [c15]Jalal Etesami, Philipp Geiger:
Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift. AAAI 2020: 10118-10125 - [i9]Jalal Etesami, Philipp Geiger:
Causal Transfer for Imitation Learning and Decision Making under Sensor-shift. CoRR abs/2003.00806 (2020) - [i8]Jalal Etesami, Christoph-Nikolas Straehle:
Non-cooperative Multi-agent Systems with Exploring Agents. CoRR abs/2005.12360 (2020)
2010 – 2019
- 2019
- [c14]William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran:
Learning Hawkes Processes Under Synchronization Noise. ICML 2019: 6325-6334 - [i7]Huang Xiao, Michael Herman, Jörg Wagner, Sebastian Ziesche, Jalal Etesami, Thai Hong Linh:
Wasserstein Adversarial Imitation Learning. CoRR abs/1906.08113 (2019) - 2018
- [j3]Anh Truong
Optimal Attack Strategies Against Predictors - Learning From Expert Advice. IEEE Trans. Inf. Forensics Secur. 13(1): 6-19 (2018) - [c13]Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, Kun Zhang:
Learning Vector Autoregressive Models With Latent Processes. AAAI 2018: 4000-4007 - 2017
- [j2]Jalal Etesami
Measuring Causal Relationships in Dynamical Systems through Recovery of Functional Dependencies. IEEE Trans. Signal Inf. Process. over Networks 3(4): 650-659 (2017) - [c12]Yingxang Yang, Jalal Etesami, Negar Kiyavash:
Efficient neighborhood selection for walk summable Gaussian graphical models. ACSSC 2017: 263-267 - [c11]Saber Salehkaleybar
Identifying nonlinear 1-step causal influences in presence of latent variables. ISIT 2017: 1341-1345 - [c10]Yingxiang Yang, Jalal Etesami, Niao He, Negar Kiyavash:
Online Learning for Multivariate Hawkes Processes. NIPS 2017: 4937-4946 - [i6]Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash:
Identifying Nonlinear 1-Step Causal Influences in Presence of Latent Variables. CoRR abs/1701.06605 (2017) - [i5]Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash:
Learning Latent Networks in Vector Auto Regressive Models. CoRR abs/1702.08575 (2017) - [i4]Jalal Etesami, Kun Zhang, Negar Kiyavash:
A New Measure of Conditional Dependence for Causal Structural Learning. CoRR abs/1704.00607 (2017) - 2016
- [j1]Jalal Etesami, Negar Kiyavash, Todd P. Coleman
Learning Minimal Latent Directed Information Polytrees. Neural Comput. 28(9): 1723-1768 (2016) - [c9]Jalal Etesami, Negar Kiyavash:
Interventional dependency graphs: An approach for discovering influence structure. ISIT 2016: 1158-1162 - [c8]Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal:
Learning Network of Multivariate Hawkes Processes: A Time Series Approach. UAI 2016 - [i3]Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal:
Learning Network of Multivariate Hawkes Processes: A Time Series Approach. CoRR abs/1603.04319 (2016) - [i2]Jalal Etesami, Negar Kiyavash:
On the Vulnerability of Digital Fingerprinting Systems to Finite Alphabet Collusion Attacks. CoRR abs/1604.08071 (2016) - 2015
- [i1]Yingxiang Yang, Jalal Etesami, Negar Kiyavash:
Efficient Neighborhood Selection for Gaussian Graphical Models. CoRR abs/1509.06449 (2015) - 2014
- [c7]Jalal Etesami, Negar Kiyavash:
Directed Information Graphs: A generalization of Linear Dynamical Graphs. ACC 2014: 2563-2568 - [c6]Jalal Etesami, Negar Kiyavash:
A novel collusion attack on finite alphabet digital fingerprinting systems. ISIT 2014: 2237-2241 - 2013
- [c5]Christopher J. Quinn, Jalal Etesami, Negar Kiyavash, Todd P. Coleman:
Robust directed tree approximations for networks of stochastic processes. ISIT 2013: 2254-2258 - 2012
- [c4]Jalal Etesami, Werner Henkel
LDPC code construction for wireless physical-layer key reconciliation. ICCC 2012: 208-213 - [c3]Jalal Etesami, Negar Kiyavash, Todd P. Coleman:
Learning minimal latent directed information trees. ISIT 2012: 2726-2730 - 2011
- [c2]Jalal Etesami, Fangning Hu, Werner Henkel
LCD Codes and Iterative Decoding by Projections, a First Step Towards an Intuitive Description of Iterative Decoding. GLOBECOM 2011: 1-4 - [c1]Jafar Mohammadi, Slawomir Stanczak, Renato L. G. Cavalcante, Jalal Etesami:
Iterative distributed channel probing for cognitive radios with power-controlled wireless links. ISWCS 2011: 567-571
Coauthor Index
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