TabKD: Tabular Knowledge Distillation through Interaction Diversity of Learned Feature Bins
cs.LG, cs.AI
Submitted: 2026-03-16
Updated: 2026-09-28
Comments: Accepted in 35th International Joint Conference on Artificial Intelligence IJCAI 2026
Journal ref: Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence 2026 Main Track. Pages 4723-4731
Code: https://github.com/PereiraMavs/int
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Model extraction from counterfactual explanations
- Data-Free Adversarial Distillation
- Contrastive Model Inversion for Data-Free Knowledge Distillation
- Distilling the Knowledge in a Neural Network
- TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
- TabTransformer: Tabular Data Modeling Using Contextual Embeddings
- TVAE: Triplet-Based Variational Autoencoder using Metric Learning
- On Learning Representations for Tabular Data Distillation
- Data-Free Knowledge Distillation for Deep Neural Networks
- FitNets: Hints for Thin Deep Nets
- Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer
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