A new model integrates covariates with grade of membership analysis for better latent structure recovery.
problem Improving latent structure recovery in multivariate categorical data analysis.
method Covariate-assisted grade of membership model exploiting shared low-rank simplex geometry.
result Auxiliary covariates can provably improve latent structure recovery, leading to faster convergence rates.
Biological and social systems consist of myriad interacting units. The interactions can be represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications s…
A new ranking model with dynamic covariates improves statistical analysis.
problem Statistical ranking with varying covariates across comparisons.
method Introduced a Plackett--Luce framework for covariate-assisted ranking, providing conditions for model identifiability and MLE existence, and developing an alternating maximization algorithm.
result Uniform consistency of the Maximum Likelihood Estimation (MLE) under suitable assumptions on graph design and covariates.
Proposes a method to recover sparse tensors with covariate info.
problem Sparse tensor with high missing entries and many zeros.
method Covariate-assisted Sparse Tensor Completion (COSTCO) using latent components.
result 23% accuracy improvement over baseline in advertisement dataset.
AdaPT-GMM improves multiple testing power with covariates.
problem Powerful and robust multiple testing with covariates.
method Covariate-assisted Gaussian mixture model with adaptive thresholding.
result AdaPT-GMM delivers high power in various scenarios.
Improved graph matching using covariates for network data integration.
problem Matching networks without unique identifiers.
method Two novel covariate-assisted seeded graph matching methods.
result Improved alignment accuracy through covariate information.
Unified method for inference on partially identified causal effects using covariates.
problem Partial identification of causal effects due to unobserved joint potential outcomes.
method Model-agnostic approach using duality theory for optimal transport problems.
result Uniformly valid inference for a wide class of estimands, even with inaccurate nuisance parameter estimates.
Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation and market segmentation. To investigate these effects, we build a time-varying network for cryptocurrencies, based on the evolution of return cross-predictability and technological similarities. We develop a …
A time-varying network reveals community structure in cryptocurrencies.
problem Investing in cryptocurrencies from different communities can diversify risk.
method Dynamic covariate-assisted spectral clustering method.
result Investors can earn 1.08% daily return by diversifying across communities.
The paper improves ranking by integrating covariates and sparse intrinsic scores.
problem Ranking items with incomplete preference scores explained by covariates.
method Extends BTL model with covariate information and sparse intrinsic scores, using penalized MLE.
result Developed debiased estimator for penalized MLE with distributional properties.
AMP algorithm for matrix tensor product model provides recovery conditions.
problem Generalization of standard spiked matrix models with multiple pairwise observations.
method Approximate message passing with optimal weighing and combining of estimates.
result Asymptotically exact performance description and necessary/sufficient recovery conditions.
Bayesian Empirical Bayes extends EB to complex structures using probabilistic symmetry.
problem Improving simultaneous inference in complex settings like arrays and graphs.
method Generalized empirical Bayes approach based on probabilistic symmetry.
result BEB outperforms existing methods in denoising arrays and spatial data.
Paper proposes CARE model for ranking with covariates, improving MLE accuracy.
problem Statistical estimation and inference for ranking with covariate information.
method Covariate-Assisted Ranking Estimation (CARE) model, extending Bradley-Terry-Luce (BTL) model.
result Derives optimal rates and asymptotic distributions for MLE of latent scores and covariates.