Although Transformer has achieved great success in natural language proc...
Machine learning has demonstrated remarkable performance over finite
dat...
Transformer-based sequential recommendation (SR) has been booming in rec...
Many real-world graph learning tasks require handling dynamic graphs whe...
Recommender Systems (RS) aim to provide personalized suggestions of item...
Existing research efforts for multi-interest candidate matching in
recom...
Contrastive learning (CL) benefits the training of sequential recommenda...
Traffic forecasting is challenging due to dynamic and complicated
spatia...
Session-based recommendation (SBR) aims to predict the user next action ...
Session-based recommendation (SBR) aims to predict the user next action ...
Sequential recommendation (SR) aims to model users' dynamic preferences ...
Side information fusion for sequential recommendation (SR) aims to
effec...
Sequential recommendation can capture user chronological preferences fro...
Automatic speech recognition (ASR) via call is essential for various
app...
Variational autoencoders (VAEs) have shown a promise in data-driven
conv...
Machine learning libraries such as TensorFlow and PyTorch simplify model...
Music highlights are valuable contents for music services. Most methods
...
Recent studies have shown remarkable success in image-to-image translati...
Computer programs written in one language are often required to be porte...
Developers often wonder how to implement a certain functionality (e.g., ...