5 papers
The Threshold Breakdown Point
Tianjun Ke, Marco Avella Medina
We introduce a novel approach to finite sample robustness that avoids the pessimism of traditional breakdown analyses. We define the threshold breakdown point, the smallest contami…
Beyond Asymptotics: Practical Insights into Community Detection in Complex Networks
Tianjun Ke, Zhiyu Xu
The stochastic block model (SBM) is a fundamental tool for community detection in networks, yet the finite-sample performance of inference methods remains underexplored. We evaluat…
MIN: Multi-channel Interaction Network for Drug-Target Interaction with Protein Distillation
Shuqi Li, Shufang Xie, Hongda Sun +4
Traditional drug discovery processes are both time-consuming and require extensive professional expertise. With the accumulation of drug-target interaction (DTI) data from experime…
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
Tianjun Ke, Haoqun Cao, Zenan Ling +1
Meta-learning has demonstrated promising results in few-shot classification (FSC) by learning to solve new problems using prior knowledge. Bayesian methods are effective at charact…
Is Score Matching Suitable for Estimating Point Processes?
Haoqun Cao, Zizhuo Meng, Tianjun Ke +1
Score matching estimators have gained widespread attention in recent years partly because they are free from calculating the integral of normalizing constant, thereby addressing th…