On Causal and Anticausal Learning
We consider the problem of function estimation in the case where an underlying causal model can be inferred. This has implications for popular scenarios such as covariate shift, concept drift, transfer learning and semi-supervised learning. We argue that causal knowledge may facilitate some approaches for a given problem, and rule out others. In particular, we formulate a hypothesis for when semi-supervised learning can help, and corroborate it with empirical results.
Code (1)
Tasks
Transfer LearningSimilar Papers 제목 키워드 기반
Physics-Based Causal Lifting Linearization of Nonlinear Control Systems Underpinned by the Koopman Operator
Methods for constructing causal linear models from nonlinear dynamical systems through lifting linearization underpinned by Koopman operator and physical system modeling theory are presented. Outputs of a nonlinear contr…
Causal vs. Anticausal merging of predictors
We study the differences arising from merging predictors in the causal and anticausal directions using the same data. In particular we study the asymmetries that arise in a simple model where we merge the predictors usin…
Inductive BiasCausal-Anticausal Decomposition of Speech using Complex Cepstrum for Glottal Source Estimation
Complex cepstrum is known in the literature for linearly separating causal and anticausal components. Relying on advances achieved by the Zeros of the Z-Transform (ZZT) technique, we here investigate the possibility of u…
Identification of non-causal systems with random switching modes (Extended Version)
We consider the identification of non-causal systems with random switching modes (NCSRSM), a class of models essential for describing typical power load management and department store inventory dynamics. The simultaneou…
Managementparameter estimationComplex Cepstrum-based Decomposition of Speech for Glottal Source Estimation
Homomorphic analysis is a well-known method for the separation of non-linearly combined signals. More particularly, the use of complex cepstrum for source-tract deconvolution has been discussed in various articles. Howev…
Articles