Summary of Power Scheduler: a Batch Size and Token Number Agnostic Learning Rate Scheduler, by Yikang Shen et al.
Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Schedulerby Yikang Shen, Matthew…
Summary of The Ultimate Guide to Fine-tuning Llms From Basics to Breakthroughs: An Exhaustive Review Of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities, by Venkatesh Balavadhani Parthasarathy et al.
The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies,…
Summary of Linear-time One-class Classification with Repeated Element-wise Folding, by Jenni Raitoharju
Linear-time One-Class Classification with Repeated Element-wise Foldingby Jenni RaitoharjuFirst submitted to arxiv on: 21 Aug…
Summary of Kolmogorov Arnold Networks in Fraud Detection: Bridging the Gap Between Theory and Practice, by Yang Lu and Felix Zhan
Kolmogorov Arnold Networks in Fraud Detection: Bridging the Gap Between Theory and Practiceby Yang Lu,…
Summary of Random Gradient Masking As a Defensive Measure to Deep Leakage in Federated Learning, by Joon Kim et al.
Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learningby Joon Kim,…
Summary of Adjusting Model Size in Continual Gaussian Processes: How Big Is Big Enough?, by Guiomar Pescador-barrios et al.
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?by Guiomar Pescador-Barrios, Sarah…
Summary of Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfaction, by Yi Wu et al.
Learned Ranking Function: From Short-term Behavior Predictions to Long-term User Satisfactionby Yi Wu, Daryl Chang,…
Summary of A Laplacian-based Quantum Graph Neural Network For Semi-supervised Learning, by Hamed Gholipour et al.
A Laplacian-based Quantum Graph Neural Network for Semi-Supervised Learningby Hamed Gholipour, Farid Bozorgnia, Kailash Hambarde,…
Summary of Learning Rate-free Reinforcement Learning: a Case For Model Selection with Non-stationary Objectives, by Aida Afshar et al.
Learning Rate-Free Reinforcement Learning: A Case for Model Selection with Non-Stationary Objectivesby Aida Afshar, Aldo…
Summary of Why Rectified Power Unit Networks Fail and How to Improve It: An Effective Theory Perspective, by Taeyoung Kim et al.
Why Rectified Power Unit Networks Fail and How to Improve It: An Effective Theory Perspectiveby…