A Hybrid Metaheuristic for the Maximum k-Plex Problem. - Krishna Reddy Gujjula; Krishnan Ayalur Seshadrinathan; Amirhossein Meisami (Examining Robustness and Vulnerability of Networked Systems, 2014)

Uncertainty quantification on simulation analysis driven by random forests. - Amirhossein Meisami; Mark P. Van Oyen; Henry Lam (WSC, 2017)

Sequential Learning under Probabilistic Constraints. - Amirhossein Meisami; Henry Lam; Chen Dong 004; Abhishek Pani (UAI, 2018)

Regret Analysis of Causal Bandit Problems. - Yangyi Lu; Amirhossein Meisami; Ambuj Tewari; Zhenyu Yan 001 (CoRR, 2019)

Constrained Reinforcement Learning via Policy Splitting. - Haoxian Chen 002; Henry Lam; Fengpei Li; Amirhossein Meisami (ACML, 2020)

Regret Analysis of Bandit Problems with Causal Background Knowledge. - Yangyi Lu; Amirhossein Meisami; Ambuj Tewari; William Yan (UAI, 2020)

Low-Rank Generalized Linear Bandit Problems. - Yangyi Lu; Amirhossein Meisami; Ambuj Tewari (AISTATS, 2021)

Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns. - Ziping Xu; Amirhossein Meisami; Ambuj Tewari (AISTATS, 2021)

Causal Bandits with Unknown Graph Structure. - Yangyi Lu; Amirhossein Meisami; Ambuj Tewari (NeurIPS, 2021)

Causal Markov Decision Processes: Learning Good Interventions Efficiently. - Yangyi Lu; Amirhossein Meisami; Ambuj Tewari (CoRR, 2021)

Efficient Reinforcement Learning with Prior Causal Knowledge. - Yangyi Lu; Amirhossein Meisami; Ambuj Tewari (CLeaR, 2022)

Generalized Bayesian Upper Confidence Bound with Approximate Inference for Bandit Problems. - Ziyi Huang; Henry Lam; Amirhossein Meisami; Haofeng Zhang 002 (CoRR, 2022)

Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework. - Ziyi Huang; Henry Lam; Amirhossein Meisami; Haofeng Zhang 002 (NeurIPS, 2023)

A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution. - Jun Tao; Qian Chen; James W. Snyder Jr.; Arava Sai Kumar; Amirhossein Meisami; Lingzhou Xue (CoRR, 2023)