arXiv:2101.05673
공식 코드 · Papers with Code
Analysis of hidden feedback loops in continuous machine learning systems
원문 초록
In this concept paper, we discuss intricacies of specifying and verifying the quality of continuous and lifelong learning artificial intelligence systems as they interact with and influence their environment causing a so-called concept drift. We signify a problem of implicit feedback loops, demonstrate how they intervene with user behavior on an exemplary housing prices prediction system. Based on a preliminary model, we highlight conditions when such feedback loops arise and discuss possible solution approaches.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Lifelong Machine Learning of Functionally Compositional Structures
Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning
LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios
UltraEdit: Training-, Subject-, and Memory-Free Lifelong Editing in Large Language Models
LiBOG: Lifelong Learning for Black-Box Optimizer Generation
LifelongAgentBench: Evaluating LLM Agents as Lifelong Learners
토론
이 논문과 연결된 포럼 글이 아직 없습니다.