research
∙
07/10/2023
Customizing Synthetic Data for Data-Free Student Learning
Data-free knowledge distillation (DFKD) aims to obtain a lightweight stu...
share
research
∙
06/11/2023
Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning
Multi-Teacher knowledge distillation provides students with additional s...
research
∙
05/31/2023
A Geometric Perspective on Diffusion Models
Recent years have witnessed significant progress in developing efficient...
research
∙
11/22/2022
Accelerating Diffusion Sampling with Classifier-based Feature Distillation
Although diffusion model has shown great potential for generating higher...
research
∙
10/25/2022
Online Cross-Layer Knowledge Distillation on Graph Neural Networks with Deep Supervision
Graph neural networks (GNNs) have become one of the most popular researc...
research
∙
08/07/2022
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization
Considerable progress has been made in domain generalization (DG) which ...
research
∙
06/07/2022
Improving Knowledge Graph Embedding via Iterative Self-Semantic Knowledge Distillation
Knowledge graph embedding (KGE) has been intensively investigated for li...
research
∙
05/05/2022
Alignahead: Online Cross-Layer Knowledge Extraction on Graph Neural Networks
Existing knowledge distillation methods on graph neural networks (GNNs) ...
research
∙
03/26/2022
Knowledge Distillation with the Reused Teacher Classifier
Knowledge distillation aims to compress a powerful yet cumbersome teache...
research
∙
02/16/2022
Deeply-Supervised Knowledge Distillation
Knowledge distillation aims to enhance the performance of a lightweight ...
research
∙
12/30/2021
Confidence-Aware Multi-Teacher Knowledge Distillation
Knowledge distillation is initially introduced to utilize additional sup...
research
∙
12/28/2021
Online Adversarial Distillation for Graph Neural Networks
Knowledge distillation has recently become a popular technique to improv...
research
∙
10/13/2021
Do We Need to Directly Access the Source Datasets for Domain Generalization?
Domain generalization (DG) aims to learn a generalizable model from mult...
research
∙
10/02/2021
Domain-Specific Bias Filtering for Single Labeled Domain Generalization
Domain generalization (DG) utilizes multiple labeled source datasets to ...
research
∙
09/14/2021
Exploring the Connection between Knowledge Distillation and Logits Matching
Knowledge distillation is a generalized logits matching technique for mo...
research
∙
08/12/2021
Distilling Holistic Knowledge with Graph Neural Networks
Knowledge Distillation (KD) aims at transferring knowledge from a larger...
research
∙
10/02/2020
Online Knowledge Distillation via Multi-branch Diversity Enhancement
Knowledge distillation is an effective method to transfer the knowledge ...
research
∙
12/01/2019
Online Knowledge Distillation with Diverse Peers
Distillation is an effective knowledge-transfer technique that uses pred...
research
∙
01/31/2019