4 papers
Sample Complexity of Nonparametric Closeness Testing for Continuous Distributions and Its Application to Causal Discovery with Hidden Confounding
Fateme Jamshidi, Sina Akbari, Negar Kiyavash
We study the problem of closeness testing for continuous distributions and its implications for causal discovery. Specifically, we analyze the sample complexity of distinguishing w…
Graph-Dependent Regret Bounds in Multi-Armed Bandits with Interference
Fateme Jamshidi, Mohammad Shahverdikondori, Negar Kiyavash
We study multi-armed bandits under network interference, where each unit's reward depends on its own treatment and those of its neighbors in a given graph. This induces an exponent…
Confounded Budgeted Causal Bandits
Fateme Jamshidi, Jalal Etesami, Negar Kiyavash
We study the problem of learning 'good' interventions in a stochastic environment modeled by its underlying causal graph. Good interventions refer to interventions that maximize re…
On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
Fateme Jamshidi, Luca Ganassali, Negar Kiyavash
Motivated by conditional independence testing, an essential step in constraint-based causal discovery algorithms, we study the nonparametric Von Mises estimator for the entropy of…