144 citations · 432 across the 16 of their papers we have counts for
6 papers · 1 filter
Revisiting Knowledge Distillation via Label Smoothing Regularization
Li Yuan, Francis E. H. Tay, Guilin Li +2
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersome teacher model into a lightweight student model. Its success is generally attributed to the privileged info…
Modular Deep Reinforcement Learning with Temporal Logic Specifications
Lim Zun Yuan, Mohammadhosein Hasanbeig, Alessandro Abate +1
We propose an actor-critic, model-free, and online Reinforcement Learning (RL) framework for continuous-state continuous-action Markov Decision Processes (MDPs) when the reward is…
Central Similarity Quantization for Efficient Image and Video Retrieval
Li Yuan, Tao Wang, Xiaopeng Zhang +4
Existing data-dependent hashing methods usually learn hash functions from pairwise or triplet data relationships, which only capture the data similarity locally, and often suffer f…
Distilling Object Detectors with Fine-grained Feature Imitation
Tao Wang, Li Yuan, Xiaopeng Zhang +1
State-of-the-art CNN based recognition models are often computationally prohibitive to deploy on low-end devices. A promising high level approach tackling this limitation is knowle…
Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
Li Yuan, Francis EH Tay, Ping Li +2
In this paper, we present a novel unsupervised video summarization model that requires no manual annotation. The proposed model termed Cycle-SUM adopts a new cycle-consistent adver…
Few-shot Adaptive Faster R-CNN
Tao Wang, Xiaopeng Zhang, Li Yuan +1
To mitigate the detection performance drop caused by domain shift, we aim to develop a novel few-shot adaptation approach that requires only a few target domain images with limited…