Adversarial Batch Inverse Reinforcement Learning: Learn to Reward from Imperfect Demonstration for Interactive Recommendation

no code implementations • 30 Oct 2023 • Jialin Liu, Xinyan Su, Zeyu He, Xiangyu Zhao, Jun Li

In this research, we focus on the problem of learning to reward (LTR), which is fundamental to reinforcement learning.

Recommendation Systems reinforcement-learning

A General Neural Causal Model for Interactive Recommendation

no code implementations • 30 Oct 2023 • Jialin Liu, Xinyan Su, Peng Zhou, Xiangyu Zhao, Jun Li

Mitigation of the survivor bias is achieved though counterfactual consistency.

counterfactual Counterfactual Inference +1

Causal Influence Maximization in Hypergraph

no code implementations • 28 Jan 2023 • Xinyan Su, Zhiheng Zhang

In many scenarios, the sum of ITEs of the infected is a more reasonable objective for influence spread, whereas it is difficult to achieve via current IM algorithms.

Causal Inference