8 papers
Prompt Perturbation for Reliable LLM Evaluation over Comparison Graphs
Dong Huang, Jianbo Sun, Pengkun Yang
Evaluating large language models (LLMs) is important for understanding their capabilities, comparing competing systems, and supporting the deployment of reliable models in practice…
Sample Complexity of Correlation Detection in Erdős-Rényi graphs
Dong Huang, Pengkun Yang
In this paper, we study correlation detection problem between a pair of Erdős-Rényi graphs. Under the null hypothesis, the two graphs are independent, whereas under the alternative…
Nonparametric Inference on Unlabeled Histograms
Yun Ma, Pengkun Yang
Statistical inference on histograms and frequency counts plays a central role in categorical data analysis. Moving beyond classical methods that directly analyze labeled frequencie…
Testing Correlation in Graphs by Counting Bounded Degree Motifs
Dong Huang, Pengkun Yang
We investigate the problem of detecting correlation between two Erdős-Rényi graphs , formulated as a hypothesis testing problem: under the null hypothesis, the two graphs a…
Identifiability and Estimation in High-Dimensional Nonparametric Latent Structure Models
Yichen Lyu, Pengkun Yang
This paper studies the problems of identifiability and estimation in high-dimensional nonparametric latent structure models. We introduce an identifiability theorem that generalize…
Sample Complexity of Correlation Detection in the Gaussian Wigner Model
Dong Huang, Pengkun Yang
Correlation analysis is a fundamental step in uncovering meaningful insights from complex datasets. In this paper, we study the problem of detecting correlations between two random…
Minimax estimation of functionals in sparse vector model with correlated observations
Yuhao Wang, Pengkun Yang, Alexandre B. Tsybakov
We consider the observations of an unknown -sparse vector corrupted by Gaussian noise with zero mean and unknown covariance matrix . We propos…
Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs
Dong Huang, Xianwen Song, Pengkun Yang
This paper studies the problem of recovering the hidden vertex correspondence between two correlated random graphs. We propose the partially correlated Erdős-Rényi graphs model, wh…