Jalal Etesami
20 papers · 2017–2026 · 8 venues · across top CS/AI venues
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Research topics
Mathematics & Optimization
(14)
Machine Learning
(13)
Artificial Intelligence
(12)
Core AI
(12)
Optimization
(8)
Optimization & Theory
(8)
Learning Types
(6)
Mathematics
(6)
Knowledge & Reasoning
(4)
Reasoning
(4)
Data Science & Analytics
(2)
Applications
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Core Methods
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Deep Learning
(1)
Reinforcement Learning
(1)
Keywords
causal inference
(6)
regret bound
(4)
causal graph
(3)
causal effect identification
(3)
causal structure
(3)
bayesian inference
(2)
multivariate hawkes process
(2)
pairwise comparison
(2)
do calculus
(2)
hitting set problem
(2)
combinatorial optimization
(2)
experiment design
(2)
temporal point process
(2)
decision making
(1)
matrix factorization
(1)
non-convex optimization
(1)
transfer learning
(1)
online learning
(1)
variational inference
(1)
regret minimization
(1)
Papers
Recycling History: Efficient Recommendations from Contextual Dueling Bandits
ALT 2026
Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations
AAAI 2026
Causal Bandits without Graph Learning
CLeaR 2025
Optimal Experiment Design for Causal Effect Identification
JMLR 2025
Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization
ICML 2025
Confounded Budgeted Causal Bandits
CLeaR 2024
Fast Proxy Experiment Design for Causal Effect Identification
NeurIPS 2024
Causal Effect Identification in Uncertain Causal Networks
NeurIPS 2023
Novel Ordering-Based Approaches for Causal Structure Learning in the Presence of Unobserved Variables
AAAI 2023
On Identifiability of Conditional Causal Effects
UAI 2023
Causal Effect Identification with Context-specific Independence Relations of Control Variables
AISTATS 2022
Learning Bayesian Networks in the Presence of Structural Side Information
AAAI 2022
Minimum Cost Intervention Design for Causal Effect Identification
ICML 2022
Revisiting the general identifiability problem
UAI 2022
Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality
NeurIPS 2022
A Variational Inference Approach to Learning Multivariate Wold Processes
AISTATS 2021
Cumulants of Hawkes Processes are Robust to Observation Noise
ICML 2021
Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift
AAAI 2020
Learning Hawkes Processes Under Synchronization Noise
ICML 2019
Online Learning for Multivariate Hawkes Processes
NeurIPS 2017