Deep learning has made substantial breakthroughs in many fields due to its powerful
automatic representation capabilities. It has been proven that neural architecture design is …

Despite the impressive progress in neural network architecture design, improving the
performance of the existing state-of-the-art models has become increasingly challenging …

Deep learning (DL) techniques have obtained remarkable achievements on various tasks,
such as image recognition, object detection, and language modeling. However, building a …

Differentiable architecture search (DARTS) provided a fast solution in finding effective
network architectures, but suffered from large memory and computing overheads in jointly …

Bi-Level Optimization (BLO) is originated from the area of economic game theory and then
introduced into the optimization community. BLO is able to handle problems with a …

Neural Architecture Search (NAS) has been explosively studied to automate the discovery of
top-performer neural networks. Current works require heavy training of supernet or intensive …

Abstract Neural Architecture Search (NAS) has attracted increasingly more attention in
recent years because of its capability to design deep neural network automatically. Among …

In the past decade, advances in deep learning have resulted in breakthroughs in a variety of
areas, including computer vision, natural language understanding, speech recognition, and …

Dataset Condensation is a newly emerging technique aiming at learning a tiny dataset that
captures the rich information encoded in the original dataset. As the size of datasets …

Object tracking has achieved significant progress over the past few years. However, state-of-
the-art trackers become increasingly heavy and expensive, which limits their deployments in …