collaborators

6 papers

stat.ME2026

Pattern-Calibrated Multimodal Prediction under Blockwise Missingness

Junhan Yu, Kejian Zhang, Doudou Zhou +1

Blockwise missingness in multimodal data is usually treated as an incomplete-input problem. We instead focus on prediction for a prespecified observed-modality pattern, where the o…

stat.ML2026

A Judge-Aware Ranking Framework for Evaluating Large Language Models without Ground Truth

Mingyuan Xu, Xinzi Tan, Jiawei Wu +1

Evaluating large language models (LLMs) on open-ended tasks without ground-truth labels is increasingly done via the LLM-as-a-judge paradigm. A critical but under-modeled issue is…

cs.LG2026

From Hawkes Processes to Attention: Time-Modulated Mechanisms for Event Sequences

Xinzi Tan, Kejian Zhang, Junhan Yu +1

Marked Temporal Point Processes (MTPPs) arise naturally in medical, social, commercial, and financial domains. However, existing Transformer-based methods mostly inject temporal in…

stat.ME2026

Preference-based Centrality and Ranking in General Metric Spaces

Lingfeng Lyu, Doudou Zhou

Ranking or assessing centrality in multivariate and non-Euclidean data is difficult because there is no canonical order and many depth notions become computationally fragile in hig…

stat.ME2026

Two-sample Testing with Block-wise Missingness in Multi-source Data

Kejian Zhang, Muxuan Liang, Robert Maile +1

Multi-source and multi-modal datasets are increasingly common in scientific research, yet they often exhibit block-wise missingness, where entire modalities are systematically abse…

stat.ME2024

MATES: Multi-view Aggregated Two-Sample Test

Zexi Cai, Wenbo Fei, Doudou Zhou

The two-sample test is a fundamental problem in statistics with a wide range of applications. In the realm of high-dimensional data, nonparametric methods have gained prominence du…