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A. Meisami

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ML4

identity via Semantic Scholar / OpenAlex

activity
20192021
most citedCausal Markov Decision Processes: Learning Good Interventions Efficiently

6 citations · 6 across the 1 of their papers we have counts for

collaborators

4 papers

stat.ML2021★ 6 cited

Causal Markov Decision Processes: Learning Good Interventions Efficiently

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari

We introduce causal Markov Decision Processes (C-MDPs), a new formalism for sequential decision making which combines the standard MDP formulation with causal structures over state…

stat.ML2020

Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns

Ziping Xu, Amirhossein Meisami, Ambuj Tewari

This paper studies the decision making problem with Funnel Structure. Funnel structure, a well-known concept in the marketing field, occurs in those systems where the decision make…

stat.ML2020

Low-Rank Generalized Linear Bandit Problems

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari

In a low-rank linear bandit problem, the reward of an action (represented by a matrix of size d1​×d2​) is the inner product between the action and an unknown low-rank matr…

stat.ML2019

Regret Analysis of Bandit Problems with Causal Background Knowledge

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari +1

We study how to learn optimal interventions sequentially given causal information represented as a causal graph along with associated conditional distributions. Causal modeling is…

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