1 citations · 2 across the 13 of their papers we have counts for
13 papers
DSS-Prompt: Dynamic-Static Synergistic Prompting for Few-Shot Class-Incremental Learning
Linpu He, Yanan Li, Bingze Li +2
Learning from large-scale pre-trained models with strong generalization ability has shown remarkable success in a wide range of downstream tasks recently, but it is still underexpl…
Crossing the Kolmogorov-Smirnov Boundary: Exact Tails, Sharp Bounds, and Broken Pivots
Elvis Han Cui, Yihao Li, Zhuang Liu
The Kolmogorov-Smirnov statistic is usually introduced as a supremum, but its finite-sample behavior is governed by a more local question: where does the empirical process first cr…
Failure of Optimal Design Theory? A Case Study in Toxicology Using Sequential Robust Optimal Design Framework
Elvis Han Cui, Michael Collins, Jessica Munson +1
This paper presents a quasi-sequential optimal design framework for toxicology experiments, specifically applied to sea urchin embryos. The authors propose a novel approach combini…
Markov Renewal Proportional Hazards is All You Need
Elvis Han Cui
Transition probability estimation plays a critical role in multi-state modeling, especially in clinical research. This paper investigates the application of semi-Markov and Markov…
A Metric-based Principal Curve Approach for Learning One-dimensional Manifold
Eliuvish Cuicizion
Principal curve is a well-known statistical method oriented in manifold learning using concepts from differential geometry. In this paper, we propose a novel metric-based principal…
PDXpower: A Power Analysis Tool for Experimental Design in Pre-clinical Xenograft Studies for Uncensored and Censored Outcomes
Shanpeng Li, Donatello Telesca, Harley I. Kornblum +5
In cancer research, leveraging patient-derived xenografts (PDXs) in pre-clinical experiments is a crucial approach for assessing innovative therapeutic strategies. Addressing the i…
Trajectory-aware Principal Manifold Framework for Data Augmentation and Image Generation
Elvis Han Cui, Bingbin Li, Yanan Li +2
Data augmentation for deep learning benefits model training, image transformation, medical imaging analysis and many other fields. Many existing methods generate new samples from a…
Applications of Nature-Inspired Metaheuristic Algorithms for Tackling Optimization Problems Across Disciplines
Elvis Han Cui, Zizhao Zhang, Culsome Junwen Chen +1
Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging op…
A Tutorial on Asymptotic Properties for Biostatisticians with Applications to COVID-19 Data
Elvis Han Cui
Asymptotic properties of statistical estimators play a significant role both in practice and in theory. However, many asymptotic results in statistics rely heavily on the independe…
D-optimal Approximate Design for Binary Regression and Quantal Response in Toxicology Studies
Elvis Han Cui
We provide a systematic treatment of -optimal design for binary regression and quantal response models in toxicology studies. For the two-parameter case, we provide an analytica…
Dual Path Structural Contrastive Embeddings for Learning Novel Objects
Bingbin Li, Elvis Han Cui, Yanan Li +2
Learning novel classes from a very few labeled samples has attracted increasing attention in machine learning areas. Recent research on either meta-learning based or transfer-learn…
Particle swarm optimization in constrained maximum likelihood estimation a case study
Elvis Cui, Dongyuan Song, Weng Kee Wong
The aim of paper is to apply two types of particle swarm optimization, global best andlocal best PSO to a constrained maximum likelihood estimation problem in pseudotime anal-ysis,…
Projection Pursuit with Applications to scRNA Sequencing Data
Elvis Han Cui, Heather Zhou
In this paper, we explore the limitations of PCA as a dimension reduction technique and study its extension, projection pursuit (PP), which is a broad class of linear dimension red…