Tag: response
-
Sparse Multiple Kernel Learning: Alternating Best Response and Semidefinite Relaxations
Sparse Multiple Kernel Learning: Alternating Best Response and Semidefinite Relaxations arXiv:2511.21890v1 Announce Type: new Abstract: We study Sparse Multiple Kernel Learning (SMKL), which is the problem of selecting a sparse convex combination of prespecified kernels for support vector binary classification. Unlike prevailing l1 regularized approaches that approximate a sparsifying penalty, we formulate the problem by…
-
Predicting Forced Responses of Probability Distributions via the Fluctuation-Dissipation Theorem and Generative Modeling
Predicting Forced Responses of Probability Distributions via the Fluctuation-Dissipation Theorem and Generative Modeling arXiv:2504.13333v1 Announce Type: new Abstract: We present a novel data-driven framework for estimating the response of higher-order moments of nonlinear stochastic systems to small external perturbations. The classical Generalized Fluctuation-Dissipation Theorem (GFDT) links the unperturbed steady-state distribution to the system’s linear response.…
-
Learning Causal Response Representations through Direct Effect Analysis
Learning Causal Response Representations through Direct Effect Analysis arXiv:2503.04358v1 Announce Type: new Abstract: We propose a novel approach for learning causal response representations. Our method aims to extract directions in which a multidimensional outcome is most directly caused by a treatment variable. By bridging conditional independence testing with causal representation learning, we formulate an optimisation…