24 citations · 59 across the 5 of their papers we have counts for
5 papers
Knowledge Distillation via Token-level Relationship Graph
Shuoxi Zhang, Hanpeng Liu, Kun He
Knowledge distillation is a powerful technique for transferring knowledge from a pre-trained teacher model to a student model. However, the true potential of knowledge transfer has…
Class-aware Information for Logit-based Knowledge Distillation
Shuoxi Zhang, Hanpeng Liu, John E. Hopcroft +1
Knowledge distillation aims to transfer knowledge to the student model by utilizing the predictions/features of the teacher model, and feature-based distillation has recently shown…
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection
Michael Tsang, Dehua Cheng, Hanpeng Liu +3
Recommendation is a prevalent application of machine learning that affects many users; therefore, it is important for recommender models to be accurate and interpretable. In this w…
Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks
Shangxing Wang, Hanpeng Liu, Pedro Henrique Gomes +1
We consider a dynamic multichannel access problem, where multiple correlated channels follow an unknown joint Markov model. A user at each time slot selects a channel to transmit d…
Reinforcement Mechanism Design, with Applications to Dynamic Pricing in Sponsored Search Auctions
Weiran Shen, Binghui Peng, Hanpeng Liu +7
In this study, we apply reinforcement learning techniques and propose what we call reinforcement mechanism design to tackle the dynamic pricing problem in sponsored search auctions…