16 citations · 90 across the 13 of their papers we have counts for
7 papers · 1 filter
SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation
Can Peng, Kun Zhao, Sam Maksoud +2
Incremental learning requires a model to continually learn new tasks from streaming data. However, traditional fine-tuning of a well-trained deep neural network on a new task will…
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition
Hsin-Pai Cheng, Feng Liang, Meng Li +5
Scale variance among different sizes of body parts and objects is a challenging problem for visual recognition tasks. Existing works usually design dedicated backbone or apply Neur…
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
Chengyue Gong, Dilin Wang, Meng Li +2
Data augmentation (DA) is an essential technique for training state-of-the-art deep learning systems. In this paper, we empirically show data augmentation might introduce noisy aug…
An efficient second-order energy stable BDF scheme for the space fractional Cahn-Hilliard equation
Yong-Liang Zhao, Meng Li, Alexander Ostermann +1
The space fractional Cahn-Hilliard phase-field model is more adequate and accurate in the description of the formation and phase change mechanism than the classical Cahn-Hilliard m…
Entangled state generation via quantum walks with multiple coins
Meng Li, Yun Shang
Generation of entangled state is of paramount importance both from quantum theoretical foundation and technology applications. Entanglement swapping provides an efficient method to…
Generalized exceptional quantum walk search
Meng Li, Yun Shang
We mainly study exceptional configuration for coined quantum walk search. For searching on a two-dimensional grid by AKR algorithm, we find some new classes of exceptional configur…
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
Dilin Wang, Meng Li, Chengyue Gong +1
Neural architecture search (NAS) has shown great promise in designing state-of-the-art (SOTA) models that are both accurate and efficient. Recently, two-stage NAS, e.g. BigNAS, dec…