Summary of Meta-task: a Method-agnostic Framework For Learning to Regularize in Few-shot Learning, by Mohammad Rostami et al.
Meta-Task: A Method-Agnostic Framework for Learning to Regularize in Few-Shot Learningby Mohammad Rostami, Atik Faysal,…
Summary of Catastrophic Overfitting: a Potential Blessing in Disguise, by Mengnan Zhao et al.
Catastrophic Overfitting: A Potential Blessing in Disguiseby Mengnan Zhao, Lihe Zhang, Yuqiu Kong, Baocai YinFirst…
Summary of Robustness Of Deep Neural Networks For Micro-doppler Radar Classification, by Mikolaj Czerkawski and Carmine Clemente and Craig Michie and Christos Tachtatzis
Robustness of Deep Neural Networks for Micro-Doppler Radar Classificationby Mikolaj Czerkawski, Carmine Clemente, Craig Michie,…
Summary of Dslr: Diversity Enhancement and Structure Learning For Rehearsal-based Graph Continual Learning, by Seungyoon Choi et al.
DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learningby Seungyoon Choi, Wonjoong Kim,…
Summary of Learning Generalization and Regularization Of Nonhomogeneous Temporal Poisson Processes, by Son Nguyen Van and Hoai Nguyen Xuan
Learning Generalization and Regularization of Nonhomogeneous Temporal Poisson Processesby Son Nguyen Van, Hoai Nguyen XuanFirst…
Summary of The Effectiveness Of Random Forgetting For Robust Generalization, by Vijaya Raghavan T Ramkumar et al.
The Effectiveness of Random Forgetting for Robust Generalizationby Vijaya Raghavan T Ramkumar, Bahram Zonooz, Elahe…
Summary of Loretta: Low-rank Economic Tensor-train Adaptation For Ultra-low-parameter Fine-tuning Of Large Language Models, by Yifan Yang et al.
LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Modelsby Yifan Yang, Jiajun…
Summary of Zerog: Investigating Cross-dataset Zero-shot Transferability in Graphs, by Yuhan Li et al.
ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphsby Yuhan Li, Peisong Wang, Zhixun Li, Jeffrey Xu…
Summary of One-bit Quantization and Sparsification For Multiclass Linear Classification with Strong Regularization, by Reza Ghane et al.
One-Bit Quantization and Sparsification for Multiclass Linear Classification with Strong Regularizationby Reza Ghane, Danil Akhtiamov,…
Summary of Fedanchor: Enhancing Federated Semi-supervised Learning with Label Contrastive Loss For Unlabeled Clients, by Xinchi Qiu et al.
FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clientsby Xinchi Qiu, Yan…