Search Results for author:
Found 6 papers, 0 papers with code
Synergistic Signals: Exploiting Co-Engagement and Semantic Links via Graph Neural Networks
Given a set of candidate entities (e. g. movie titles), the ability to identify similar entities is a core capability of many recommender systems.
InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models
Our studies lead us to design and build a new solution for data pipeline optimization, InTune.
On Negative Sampling for Audio-Visual Contrastive Learning from Movies
The abundance and ease of utilizing sound, along with the fact that auditory clues reveal a plethora of information about what happens in a scene, make the audio-visual space an intuitive choice for representation learning.
Detection of Deepfake Videos Using Long Distance Attention
And a spatial-temporal model is proposed which has two components for capturing spatial and temporal forgery traces in global perspective respectively.
Watching Too Much Television is Good: Self-Supervised Audio-Visual Representation Learning from Movies and TV Shows
The abundance and ease of utilizing sound, along with the fact that auditory clues reveal so much about what happens in the scene, make the audio-visual space a perfectly intuitive choice for self-supervised representation learning.
Locality-Aware Rotated Ship Detection in High-Resolution Remote Sensing Imagery Based on Multi-Scale Convolutional Network
Ship detection has been an active and vital topic in the field of remote sensing for a decade, but it is still a challenging problem due to the large scale variations, the high aspect ratios, the intensive arrangement, and the background clutter disturbance.
