Cross-modal distillation has been widely used to transfer knowledge acro...
It is a long-standing open question to construct a classical oracle rela...
We study a parameterized version of the local Hamiltonian problem, calle...
Although more layers and more parameters generally improve the accuracy ...
Unclonable encryption, first introduced by Broadbent and Lord (TQC'20), ...
The advent of large-scale pre-trained language models has contributed gr...
Uncertainty estimation for unlabeled data is crucial to active learning....
Pre-training has been a popular learning paradigm in deep learning era,
...
Central to active learning (AL) is what data should be selected for
anno...
Fine-tuning pre-trained language models such as BERT has become a common...
To improve the performance of deep learning, mixup has been proposed to ...
Deep neural networks have been well-known for their superb performance i...
While recent studies on semi-supervised learning have shown remarkable
p...
Temporal relational modeling in video is essential for human action
unde...
Fine-tuning deep neural networks pre-trained on large scale datasets is ...
Estimation of the information content in a neural network model can be
p...
Transferring knowledge from large source datasets is an effective way to...
Fine-tuning the deep convolution neural network(CNN) using a pre-trained...
A normalizing flow is an invertible mapping between an arbitrary probabi...
Softening labels of training datasets with respect to data representatio...
In this paper, we study the problem of joint active and passive beamform...
Transfer learning have been frequently used to improve deep neural netwo...
Regularization of Deep Neural Networks (DNNs) for the sake of improving ...
Transfer learning through fine-tuning a pre-trained neural network with ...
In this paper, we studied the problem of beam alignment for millimeter w...
We consider the problem of spectrum sharing in a cognitive radio system
...
We consider the problem of spectrum sharing in a cognitive radio system
...