4 citations · 4 across the 2 of their papers we have counts for
4 papers
Large Language Model Enhanced Machine Learning Estimators for Classification
Yuhang Wu, Yingfei Wang, Chu Wang +1
Pre-trained large language models (LLM) have emerged as a powerful tool for simulating various scenarios and generating output given specific instructions and multimodal input. In…
Optimal Learning for Sequential Decision Making for Expensive Cost Functions with Stochastic Binary Feedbacks
Yingfei Wang, Chu Wang, Warren Powell
We consider the problem of sequentially making decisions that are rewarded by "successes" and "failures" which can be predicted through an unknown relationship that depends on a pa…
Functional Frank-Wolfe Boosting for General Loss Functions
Chu Wang, Yingfei Wang, Weinan E +1
Boosting is a generic learning method for classification and regression. Yet, as the number of base hypotheses becomes larger, boosting can lead to a deterioration of test performa…
The Knowledge Gradient with Logistic Belief Models for Binary Classification
Yingfei Wang, Chu Wang, Warren Powell
We consider sequential decision making problems for binary classification scenario in which the learner takes an active role in repeatedly selecting samples from the action pool an…