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Found 7 papers, 5 papers with code
Multi-Granularity Click Confidence Learning via Self-Distillation in Recommendation
Due to the lack of supervised signals in click confidence, we first apply self-supervised learning to obtain click confidence scores via a global self-distillation method.
FishMOT: A Simple and Effective Method for Fish Tracking Based on IoU Matching
Wherein, a basic module performs target association based on IoU of detection boxes between successive frames to deal with morphological change of fish; an interaction module combines IoU of detection boxes and IoU of fish entity to handle occlusions; a refind module use spatio-temporal information uses spatio-temporal information to overcome the tracking failure resulting from the missed detection by the detector under complex environment.
Learning from All Sides: Diversified Positive Augmentation via Self-distillation in Recommendation
A powerful positive item augmentation is beneficial to address the sparsity issue, while few works could jointly consider both the accuracy and diversity of these augmented training labels.
Explainable Equivariant Neural Networks for Particle Physics: PELICAN
PELICAN is a novel permutation equivariant and Lorentz invariant or covariant aggregator network designed to overcome common limitations found in architectures applied to particle physics problems.
UFNRec: Utilizing False Negative Samples for Sequential Recommendation
To this end, we propose a novel method that can Utilize False Negative samples for sequential Recommendation (UFNRec) to improve model performance.
Light Field Depth Estimation via Stitched Epipolar Plane Images
This strategy involves determining the depth of such regions by progressing from the edges towards the interior, prioritizing accurate regions over coarse regions.
CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation
State-of-the-art sequential recommendation models proposed very recently combine contrastive learning techniques for obtaining high-quality user representations.
