Search Results for author:
Found 15 papers, 4 papers with code
Watch out Venomous Snake Species: A Solution to SnakeCLEF2023
The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata.
DynamicKD: An Effective Knowledge Distillation via Dynamic Entropy Correction-Based Distillation for Gap Optimizing
This paper proposes a novel knowledge distillation algorithm based on dynamic entropy correction to reduce the gap by adjusting the student instead of the teacher.
Investigating Chain-of-thought with ChatGPT for Stance Detection on Social Media
Stance detection predicts attitudes towards targets in texts and has gained attention with the rise of social media.
FedACK: Federated Adversarial Contrastive Knowledge Distillation for Cross-Lingual and Cross-Model Social Bot Detection
In particular, a global generator is used to extract the knowledge of global data distribution and distill it into each client's local model.
CORE: Learning Consistent Ordinal REpresentations for Image Ordinal Estimation
However, the manifold of the resultant feature representations does not maintain the intrinsic ordinal relations of interest, which hinders the effectiveness of the image ordinal estimation.
RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture Search
More specifically, we consider the social bot detection problem as a user-centric subgraph embedding and classification task.
Deep reinforcement learning guided graph neural networks for brain network analysis
Modern neuroimaging techniques, such as diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), enable us to model the human brain as a brain network or connectome.
Location-Free Camouflage Generation Network
However, these methods struggle in 1) efficiently generating camouflage images using foreground and background with arbitrary structure; 2) camouflaging foreground objects to regions with multiple appearances (e. g. the junction of the vegetation and the mountains), which limit their practical application.
RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition
Recently, a massive number of deep learning based approaches have been successfully applied to various remote sensing image (RSI) recognition tasks.
Label Distribution Amendment with Emotional Semantic Correlations for Facial Expression Recognition
Based on this, we propose a new method that amends the label distribution of each facial image by leveraging correlations among expressions in the semantic space.
Facial Expression Recognition
Facial Expression Recognition (FER)
Locate Who You Are: Matching Geo-location to Text for User Identity Linkage
However, encouraged by online services, users would also post asymmetric information across networks, such as geo-locations and texts.
Efficient High-Dimensional Data Representation Learning via Semi-Stochastic Block Coordinate Descent Methods
To address this issue, we propose a novel hard thresholding algorithm, called Semi-stochastic Block Coordinate Descent Hard Thresholding Pursuit (SBCD-HTP).
Curvature-aware Manifold Learning
The purpose of our algorithm is to break the local isometry assumption and to reduce the dimension of the general manifold which is not isometric to Euclidean space.
Locality preserving projection on SPD matrix Lie group: algorithm and analysis
Our work is based on the fact that the set of all SPD matrices with the same size has a Lie group structure, and we aim to transform the manifold learning to the SPD matrix Lie group.
Applying Ricci Flow to High Dimensional Manifold Learning
Traditional manifold learning algorithms often bear an assumption that the local neighborhood of any point on embedded manifold is roughly equal to the tangent space at that point without considering the curvature.
