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Found 7 papers, 5 papers with code
Moreau Envelope Based Difference-of-weakly-Convex Reformulation and Algorithm for Bilevel Programs
In a recent study by Ye et al. (2023), a value function-based difference of convex algorithm was introduced to address bilevel programs.
Generalized Data Thinning Using Sufficient Statistics
A recent paper showed that for some well-known natural exponential families, $X$ can be "thinned" into independent random variables $X^{(1)}, \ldots, X^{(K)}$, such that $X = \sum_{k=1}^K X^{(k)}$.
Data thinning for convolution-closed distributions
We propose data thinning, an approach for splitting an observation into two or more independent parts that sum to the original observation, and that follow the same distribution as the original observation, up to a (known) scaling of a parameter.
Tree-Values: selective inference for regression trees
A naive approach to inference that does not account for the fact that the tree was estimated from the data will not achieve standard guarantees, such as Type 1 error rate control and nominal coverage.
Selective Inference for Hierarchical Clustering
Classical tests for a difference in means control the type I error rate when the groups are defined a priori.
Testing for Association in Multi-View Network Data
To answer this question, we extend the stochastic block model for a single network view to the two-view setting, and develop a new hypothesis test for the null hypothesis that the latent community memberships in the two data views are independent.
Are Clusterings of Multiple Data Views Independent?
However, clustering the participants based on multiple data views implicitly assumes that a single underlying clustering of the participants is shared across all data views.
