Zero Redundancy Optimizer (ZeRO) has been used to train a wide range of ...
Existing end-to-end Multi-Object Tracking (e2e-MOT) methods have not
sur...
This is a brief technical report of our proposed method for Multiple-Obj...
The interaction and dimension of points are two important axes in design...
Cloud object storage such as AWS S3 is cost-effective and highly elastic...
In recent years, the landscape of computing paradigms has witnessed a gr...
Graph Neural Networks (GNNs) is a promising approach for applications wi...
The rise of deep neural networks provides an important driver in optimiz...
In today's production machine learning (ML) systems, models are continuo...
With the advancement of machine learning (ML) and its growing awareness,...
In this paper, we analyze the impact of information freshness on supervi...
Data heterogeneity has been identified as one of the key features in
fed...
Scale variance among different sizes of body parts and objects is a
chal...
Neural Architecture Search (NAS) automates and prospers the design of ne...
Modern deep neural networks (DNNs) often require high memory consumption...
Internet-scale web applications are becoming increasingly storage-intens...
Federated Learning (FL) enables learning a shared model across many clie...
The interoperability across multiple blockchains would play a critical r...
Resource is an important constraint when deploying Deep Neural Networks
...
In this paper, we propose Efficient Progressive Neural Architecture Sear...
Designing neural architectures for edge devices is subject to constraint...
We propose AutoGrow to automate depth discovery in Deep Neural Networks
...
Blockchain is an enabler of many emerging decentralized applications in ...
Distributed learning systems have enabled training large-scale models ov...
Neural networks have shown great performance in cognitive tasks. When
de...
In distributed deep learning, a large batch size in Stochastic Gradient
...
High network communication cost for synchronizing gradients and paramete...
We face network data from various sources, such as protein interactions ...