Search Results for author:
Found 11 papers, 7 papers with code
Low-Rank Graph Contrastive Learning for Node Classification
To the best of our knowledge, our theoretical result is among the first to theoretically demonstrate the advantage of low-rank learning in graph contrastive learning supported by strong empirical performance.
A Learning-based Declarative Privacy-Preserving Framework for Federated Data Management
It is challenging to balance the privacy and accuracy for federated query processing over multiple private data silos.
RecMind: Large Language Model Powered Agent For Recommendation
While the recommendation system (RS) has advanced significantly through deep learning, current RS approaches usually train and fine-tune models on task-specific datasets, limiting their generalizability to new recommendation tasks and their ability to leverage external knowledge due to model scale and data size constraints.
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation
In this paper, we propose Robust Neural Architecture Search by Cross-Layer Knowledge Distillation (RNAS-CL), a novel NAS algorithm that improves the robustness of NAS by learning from a robust teacher through cross-layer knowledge distillation.
FEC: Fast Euclidean Clustering for Point Cloud Segmentation
Segmentation from point cloud data is essential in many applications such as remote sensing, mobile robots, or autonomous cars.
Bayesian Robust Graph Contrastive Learning
In this work, we propose a novel and robust method, Bayesian Robust Graph Contrastive Learning (BRGCL), which trains a GNN encoder to learn robust node representations.
Adaptive Cross-Layer Attention for Image Restoration
Non-local attention module has been proven to be crucial for image restoration.
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning
In general, the contrastive learning process in GCL is performed on top of the representations learned by a graph neural network (GNN) backbone, which transforms and propagates the node contextual information based on its local neighborhoods.
ECML: An Ensemble Cascade Metric Learning Mechanism towards Face Verification
Embedding RMML into the proposed ECML mechanism, our metric learning paradigm (EC-RMML) can run in the one-pass learning manner.
3DV: 3D Dynamic Voxel for Action Recognition in Depth Video
Each available 3DV voxel intrinsically involves 3D spatial and motion feature jointly.
Action Recognition for Depth Video using Multi-view Dynamic Images
To better exploit three-dimensional (3D) characteristics, multi-view dynamic images are proposed.
