Knowledge distillation addresses the problem of transferring knowledge f...
Traditional wall-sized displays mostly only support side-by-side co-loca...
The text retrieval task is mainly performed in two ways: the bi-encoder
...
Due to the rising complexity of the metaverse's business logic and the
l...
De novo peptide sequencing from mass spectrometry data is an important m...
Studies of active learning traditionally assume the target and source da...
Due to balanced accuracy and speed, joint learning detection and ReID-ba...
The detection of thoracic abnormalities challenge is organized by the
De...
Recent work (Feng et al., 2018) establishes the presence of short,
unint...
Progress in cross-lingual modeling depends on challenging, realistic, an...
A good object segmentation should contain clear contours and complete
re...
We propose a new application of embedding techniques for problem retriev...
Power system state estimation plays a fundamental and critical role in t...
The expressiveness of search space is a key concern in neural architectu...
Semantic segmentation with deep learning has achieved great progress in
...
To produce a domain-agnostic question answering model for the Machine Re...
In a comprehensive cohort study of two competing treatments (say, A and ...
A novel centerline extraction framework is reported which combines an
en...
Data replication is crucial in modern distributed systems as a means to
...
Power flow analysis plays a fundamental and critical role in the energy
...
In this paper, we present STAR, a new distributed in-memory database wit...
In this paper, we present STAR, a new distributed and replicated in-memo...
Compared with traditional relational database, graph database, GDB, is a...
Pioneered by Google's Pregel, many distributed systems have been develop...
Massive graphs, such as online social networks and communication network...