Jalal Etesami - RankMe

64 papers A* 12A 5B 6C 2Misc 1Journal 34Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Clinically Meaningful Explainability for NeuroAI: An ethical, technical, and clinical perspective. CoRR Laura Schopp, Ambra DImperio, Jalal Etesami, Marcello Ienca
2026	J	`jnl`	Consensus-based optimization (CBO): Towards Global Optimality in Robotics. CoRR Xudong Sun, Armand Jordana, Massimo Fornasier, Jalal Etesami, Majid Khadiv
2026	J	`jnl`	Global Convergence to Nash Equilibrium in Nonconvex General-Sum Games under the CoRR Yutong Chao, Jalal Etesami
2026	A*	`conf`	Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations. AAAI Larkin Liu, Kashif Rasul, Yutong Chao, Jalal Etesami
2025	—	`conf`	Causal Bandits without Graph Learning. CLeaR Mikhail Konobeev, Jalal Etesami, Negar Kiyavash
2025	J	`jnl`	Graph Learning is Suboptimal in Causal Bandits. CoRR Mohammad Shahverdikondori, Jalal Etesami, Negar Kiyavash
2025	J	`jnl`	Online Mixture of Experts: No-Regret Learning for Optimal Collective Decision-Making. CoRR Larkin Liu, Jalal Etesami
2025	J	`jnl`	Optimal Experiment Design for Causal Effect Identification. J. Mach. Learn. Res. Sina Akbari, Jalal Etesami, Negar Kiyavash
2025	J	`jnl`	Recommendations from Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization. CoRR Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser
2025	A*	`conf`	Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization. ICML Suryanarayana Sankagiri, Jalal Etesami, Matthias Grossglauser
2025	J	`jnl`	Recycling History: Efficient Recommendations from Contextual Dueling Bandits. CoRR Suryanarayana Sankagiri, Jalal Etesami, Pouria Fatemi, Matthias Grossglauser
2025	J	`jnl`	Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations. CoRR Larkin Liu, Kashif Rasul, Yutong Chao, Jalal Etesami
2024	—	`conf`	Confounded Budgeted Causal Bandits. CLeaR Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
2024	J	`jnl`	Confounded Budgeted Causal Bandits. CoRR Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
2024	A*	`conf`	Fast Proxy Experiment Design for Causal Effect Identification. NeurIPS Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran
2024	J	`jnl`	Fast Proxy Experiment Design for Causal Effect Identification. CoRR Sepehr Elahi, Sina Akbari, Jalal Etesami, Negar Kiyavash, Patrick Thiran
2023	J	`jnl`	Analysis of Large Market Data Using Neural Networks: A Causal Approach. IEEE J. Sel. Areas Inf. Theory Marc-Aurèle Divernois, Jalal Etesami, Damir Filipovic, Negar Kiyavash
2023	J	`jnl`	Causal Bandits without Graph Learning. CoRR Mikhail Konobeev, Jalal Etesami, Negar Kiyavash
2023	A*	`conf`	Causal Effect Identification in Uncertain Causal Networks. NeurIPS Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash
2023	J	`jnl`	Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework. CoRR Jalal Etesami, Ali Habibnia, Negar Kiyavash
2023	A*	`conf`	Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. AAAI Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash
2023	A	`conf`	On Identifiability of Conditional Causal Effects. UAI Yaroslav Kivva, Jalal Etesami, Negar Kiyavash
2023	J	`jnl`	On Identifiability of Conditional Causal Effects. CoRR Yaroslav Kivva, Jalal Etesami, Negar Kiyavash
2022	J	`jnl`	A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics. CoRR Matthew J. Vowels, Sina Akbari, Jalal Etesami, Necati Cihan Camgöz, Richard Bowden
2022	J	`jnl`	Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect. CoRR Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash
2022	A	`conf`	Causal Effect Identification with Context-specific Independence Relations of Control Variables. AISTATS Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
2022	A*	`conf`	Learning Bayesian Networks in the Presence of Structural Side Information. AAAI Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
2022	A*	`conf`	Minimum Cost Intervention Design for Causal Effect Identification. ICML Sina Akbari, Jalal Etesami, Negar Kiyavash
2022	J	`jnl`	Minimum Cost Intervention Design for Causal Effect Identification. CoRR Sina Akbari, Jalal Etesami, Negar Kiyavash
2022	J	`jnl`	Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables. CoRR Ehsan Mokhtarian, Mohammadsadegh Khorasani, Jalal Etesami, Negar Kiyavash
2022	J	`jnl`	Revisiting the General Identifiability Problem. CoRR Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash
2022	A	`conf`	Revisiting the general identifiability problem. UAI Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash
2022	A*	`conf`	Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality. NeurIPS Ilyas Fatkhullin, Jalal Etesami, Niao He, Negar Kiyavash
2021	A	`conf`	A Variational Inference Approach to Learning Multivariate Wold Processes. AISTATS Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran
2021	J	`jnl`	Causal Effect Identification with Context-specific Independence Relations of Control Variables. CoRR Ehsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
2021	A*	`conf`	Cumulants of Hawkes Processes are Robust to Observation Noise. ICML William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran
2021	J	`jnl`	Learning Bayesian Networks in the Presence of Structural Side Information. CoRR Ehsan Mokhtarian, Sina Akbari, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
2020	A*	`conf`	Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift. AAAI Jalal Etesami, Philipp Geiger
2020	J	`jnl`	Causal Transfer for Imitation Learning and Decision Making under Sensor-shift. CoRR Jalal Etesami, Philipp Geiger
2020	J	`jnl`	Non-cooperative Multi-agent Systems with Exploring Agents. CoRR Jalal Etesami, Christoph-Nikolas Straehle
2019	A*	`conf`	Learning Hawkes Processes Under Synchronization Noise. ICML William Trouleau, Jalal Etesami, Matthias Grossglauser, Negar Kiyavash, Patrick Thiran
2019	J	`jnl`	Wasserstein Adversarial Imitation Learning. CoRR Huang Xiao, Michael Herman, Jörg Wagner, Sebastian Ziesche, Jalal Etesami, Thai Hong Linh
2018	A*	`conf`	Learning Vector Autoregressive Models With Latent Processes. AAAI Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash, Kun Zhang
2018	J	`jnl`	Optimal Attack Strategies Against Predictors - Learning From Expert Advice. IEEE Trans. Inf. Forensics Secur. Anh Truong, S. Rasoul Etesami, Jalal Etesami, Negar Kiyavash
2017	J	`jnl`	A New Measure of Conditional Dependence for Causal Structural Learning. CoRR Jalal Etesami, Kun Zhang, Negar Kiyavash
2017	Misc	`conf`	Efficient neighborhood selection for walk summable Gaussian graphical models. ACSSC Yingxang Yang, Jalal Etesami, Negar Kiyavash
2017	J	`jnl`	Identifying Nonlinear 1-Step Causal Influences in Presence of Latent Variables. CoRR Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash
2017	B	`conf`	Identifying nonlinear 1-step causal influences in presence of latent variables. ISIT Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash
2017	J	`jnl`	Learning Latent Networks in Vector Auto Regressive Models. CoRR Saber Salehkaleybar, Jalal Etesami, Negar Kiyavash
2017	J	`jnl`	Measuring Causal Relationships in Dynamical Systems through Recovery of Functional Dependencies. IEEE Trans. Signal Inf. Process. over Networks Jalal Etesami, Negar Kiyavash
2017	—	`conf`	Online Learning for Multivariate Hawkes Processes. NIPS Yingxiang Yang, Jalal Etesami, Niao He, Negar Kiyavash
2016	B	`conf`	Interventional dependency graphs: An approach for discovering influence structure. ISIT Jalal Etesami, Negar Kiyavash
2016	J	`jnl`	Learning Minimal Latent Directed Information Polytrees. Neural Comput. Jalal Etesami, Negar Kiyavash, Todd P. Coleman
2016	A	`conf`	Learning Network of Multivariate Hawkes Processes: A Time Series Approach. UAI Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal
2016	J	`jnl`	Learning Network of Multivariate Hawkes Processes: A Time Series Approach. CoRR Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal
2016	J	`jnl`	On the Vulnerability of Digital Fingerprinting Systems to Finite Alphabet Collusion Attacks. CoRR Jalal Etesami, Negar Kiyavash
2015	J	`jnl`	Efficient Neighborhood Selection for Gaussian Graphical Models. CoRR Yingxiang Yang, Jalal Etesami, Negar Kiyavash
2014	B	`conf`	A novel collusion attack on finite alphabet digital fingerprinting systems. ISIT Jalal Etesami, Negar Kiyavash
2014	C	`conf`	Directed Information Graphs: A generalization of Linear Dynamical Graphs. ACC Jalal Etesami, Negar Kiyavash
2013	B	`conf`	Robust directed tree approximations for networks of stochastic processes. ISIT Christopher J. Quinn, Jalal Etesami, Negar Kiyavash, Todd P. Coleman
2012	C	`conf`	LDPC code construction for wireless physical-layer key reconciliation. ICCC Jalal Etesami, Werner Henkel
2012	B	`conf`	Learning minimal latent directed information trees. ISIT Jalal Etesami, Negar Kiyavash, Todd P. Coleman
2011	—	`conf`	Iterative distributed channel probing for cognitive radios with power-controlled wireless links. ISWCS Jafar Mohammadi, Slawomir Stanczak, Renato L. G. Cavalcante, Jalal Etesami
2011	B	`conf`	LCD Codes and Iterative Decoding by Projections, a First Step Towards an Intuitive Description of Iterative Decoding. GLOBECOM Jalal Etesami, Fangning Hu, Werner Henkel