Summary of Hessian-free Online Certified Unlearning, by Xinbao Qiao et al.
Hessian-Free Online Certified Unlearningby Xinbao Qiao, Meng Zhang, Ming Tang, Ermin WeiFirst submitted to arxiv…
Summary of A (more) Realistic Evaluation Setup For Generalisation Of Community Models on Malicious Content Detection, by Ivo Verhoeven et al.
A (More) Realistic Evaluation Setup for Generalisation of Community Models on Malicious Content Detectionby Ivo…
Summary of What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks, by Xingwu Chen et al.
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasksby Xingwu Chen,…
Summary of Information Plane Analysis Visualization in Deep Learning Via Transfer Entropy, by Adrian Moldovan et al.
Information Plane Analysis Visualization in Deep Learning via Transfer Entropyby Adrian Moldovan, Angel Cataron, Razvan…
Summary of Can Biases in Imagenet Models Explain Generalization?, by Paul Gavrikov and Janis Keuper
Can Biases in ImageNet Models Explain Generalization?by Paul Gavrikov, Janis KeuperFirst submitted to arxiv on:…
Summary of Make Continual Learning Stronger Via C-flat, by Ang Bian et al.
Make Continual Learning Stronger via C-Flatby Ang Bian, Wei Li, Hangjie Yuan, Chengrong Yu, Mang…
Summary of Chain: Enhancing Generalization in Data-efficient Gans Via Lipschitz Continuity Constrained Normalization, by Yao Ni et al.
CHAIN: Enhancing Generalization in Data-Efficient GANs via lipsCHitz continuity constrAIned Normalizationby Yao Ni, Piotr KoniuszFirst…
Summary of Dilm: Distilling Dataset Into Language Model For Text-level Dataset Distillation, by Aru Maekawa et al.
DiLM: Distilling Dataset into Language Model for Text-level Dataset Distillationby Aru Maekawa, Satoshi Kosugi, Kotaro…
Summary of Revisiting Random Weight Perturbation For Efficiently Improving Generalization, by Tao Li et al.
Revisiting Random Weight Perturbation for Efficiently Improving Generalizationby Tao Li, Qinghua Tao, Weihao Yan, Zehao…
Summary of Learning Using Granularity Statistical Invariants For Classification, by Ting-ting Zhu et al.
Learning using granularity statistical invariants for classificationby Ting-Ting Zhu, Yuan-Hai Shao, Chun-Na Li, Tian LiuFirst…