What Sketch Explainability Really Means for Downstream Tasks?

H Bandyopadhyay, PN Chowdhury… - Proceedings of the …, 2024 - openaccess.thecvf.com
In this paper we explore the unique modality of sketch for explainability emphasising the
profound impact of human strokes compared to conventional pixel-oriented studies. Beyond …

Positivity-free policy learning with observational data

P Zhao, A Chambaz, J Josse… - … Conference on Artificial …, 2024 - proceedings.mlr.press
Policy learning utilizing observational data is pivotal across various domains, with the
objective of learning the optimal treatment assignment policy while adhering to specific …

Individualized Policy Evaluation and Learning under Clustered Network Interference

Y Zhang, K Imai - arXiv preprint arXiv:2311.02467, 2023 - arxiv.org
While there now exists a large literature on policy evaluation and learning, much of prior
work assumes that the treatment assignment of one unit does not affect the outcome of …

The Cram Method for Efficient Simultaneous Learning and Evaluation

Z Jia, K Imai, ML Li - arXiv preprint arXiv:2403.07031, 2024 - arxiv.org
We introduce the" cram" method, a general and efficient approach to simultaneous learning
and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched …

Topics in causal inférence and policy learning with applications to precision medicine

P Zhao - 2024 - theses.hal.science
Causality is a fundamental concept in science and philosophy, and with the increasing
complexity of data collection and structure, statistics plays a pivotal role in inferring causes …