Saber Salehkaleybar
21 papers · 2017–2026 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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Research topics
Artificial Intelligence
(17)
Core AI
(16)
Machine Learning
(15)
Optimization & Theory
(13)
Knowledge & Reasoning
(8)
Reasoning
(8)
Mathematics & Optimization
(7)
Optimization
(5)
Learning Types
(3)
Deep Learning
(2)
Core Methods
(2)
Learning Paradigms
(2)
Mathematics
(2)
Reinforcement Learning
(1)
Bayesian & Probabilistic
(1)
Keywords
causal discovery
(6)
causal inference
(6)
causal effect
(4)
structural causal model
(3)
latent confounder
(3)
experiment design
(3)
one-shot learning
(2)
sample complexity
(2)
reinforcement learning
(2)
directed acyclic graph
(2)
causal graph
(2)
latent variable
(2)
distributed optimization
(2)
multi-resolution estimator
(2)
causal structure
(2)
variance reduction
(2)
communication efficiency
(2)
distributed learning
(1)
causal effect estimation
(1)
stochastic gradient descent
(1)
Papers
Learning Subgroups with Maximum Treatment Effects Without Causal Heuristics
AAAI 2026
Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems
UAI 2026
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
UAI 2025
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
ICML 2025
Efficiently Escaping Saddle Points for Policy Optimization
UAI 2025
Hierarchical Reinforcement Learning with Targeted Causal Interventions
ICML 2025
MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters
ICML 2025
Multi-Domain Causal Discovery in Bijective Causal Models
CLeaR 2025
Causal Effect Identification in LiNGAM Models with Latent Confounders
ICML 2024
Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data
AISTATS 2024
A Cross-Moment Approach for Causal Effect Estimation
NeurIPS 2023
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
JMLR 2023
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions
NeurIPS 2022
One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them
JMLR 2021
Bounds on Over-Parameterization for Guaranteed Existence of Descent Paths in Shallow ReLU Networks
ICLR 2020
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
ICML 2020
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables
JMLR 2020
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees
AAAI 2019
Order Optimal One-Shot Distributed Learning
NeurIPS 2019
Budgeted Experiment Design for Causal Structure Learning
ICML 2018
Learning Causal Structures Using Regression Invariance
NeurIPS 2017