paper-with-me

Papers

Info Intervention

2019-07-24 · Gong Heyang, Zhu Ke

Causal diagrams based on do intervention are useful tools to formalize, process and understand causal relationship among variables. However, the do intervention has controversial interpretation of causal questions for non-manipulable variables, and it also lacks the power to check the conditions related to counterfactual variables. This paper introduces a new info intervention to tackle these two problems, and provides causal diagrams for communication and theoretical focus based on this info intervention. Our info intervention intervenes the input/output information of causal mechanisms, while the do intervention intervenes the causal mechanisms. Consequently, the causality is viewed as information transfer in the info intervention framework. As an extension, the generalized info intervention is also proposed and studied in this paper.

📄 PDF Abstract BibTeX arXiv:1907.11090

Code (0)

등록된 구현이 없습니다.

Tasks

Causal Inferencecounterfactual

Methods 이 논문이 사용한 방법론

INFO This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean…

Similar Papers 제목 키워드 기반

The Geometry of Learning to Avoid Interventions

2026-02-03 · Ethan Pronovost, Khimya Khetarpal, Siddhartha Srinivasa arxiv

Human interventions are a common source of supervision in autonomous systems during deployment. Many existing approaches are based on avoiding interventions, yet the consequences of this objective are not well understood…

Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach

2023-07-13 · Mahmoud Shoush, Marlon Dumas

Prescriptive process monitoring methods seek to optimize the performance of business processes by triggering interventions at runtime, thereby increasing the probability of positive case outcomes. These interventions are…

Conformal Predictionreinforcement-learningReinforcement Learning

Designing and evaluating an online reinforcement learning agent for physical exercise recommendations in N-of-1 trials

2023-09-25 · Dominik Meier, Ipek Ensari, Stefan Konigorski

Personalized adaptive interventions offer the opportunity to increase patient benefits, however, there are challenges in their planning and implementation. Once implemented, it is an important question whether personaliz…

reinforcement-learningReinforcement Learning

Predicting Intervention Approval in Clinical Trials through Multi-Document Summarization

2022-04-01 · ACL 2022 5 · Georgios Katsimpras, Georgios Paliouras

Clinical trials offer a fundamental opportunity to discover new treatments and advance the medical knowledge. However, the uncertainty of the outcome of a trial can lead to unforeseen costs and setbacks. In this study, w…

ArticlesDocument SummarizationMulti-Document SummarizationSentence

Can Information Flows Suggest Targets for Interventions in Neural Circuits?

2021-11-09 · NeurIPS 2021 12 · Praveen Venkatesh, Sanghamitra Dutta, Neil Mehta, Pulkit Grover

Motivated by neuroscientific and clinical applications, we empirically examine whether observational measures of information flow can suggest interventions. We do so by performing experiments on artificial neural network…

AttributeFairness