6 citations · 26 across the 7 of their papers we have counts for
7 papers
A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution
Jun Tao, Qian Chen, James W. Snyder +3
Marketers employ various online advertising channels to reach customers, and they are particularly interested in attribution for measuring the degree to which individual touchpoint…
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Ziyi Huang, Henry Lam, Amirhossein Meisami +1
Bayesian bandit algorithms with approximate Bayesian inference have been widely used in real-world applications. However, there is a large discrepancy between the superior practica…
Causal Bandits with Unknown Graph Structure
Yangyi Lu, Amirhossein Meisami, Ambuj Tewari
In causal bandit problems, the action set consists of interventions on variables of a causal graph. Several researchers have recently studied such bandit problems and pointed out t…
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…
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…
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 ) is the inner product between the action and an unknown low-rank matr…