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329 posts in total. Keep on posting.
Showing posts 313–324 of 329. Each entry opens locally on this site; legacy Hexo posts link back to their original article at the bottom for reference.
2021
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Reinforcement Learning-Principle-Day6
Reinforcement learning study notes — policy gradient methods: REINFORCE, Actor-Critic, and A2C algorithms.
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Reinforcement Learning-Principle-Day5
Reinforcement learning study notes — function approximation and the DQN (Deep Q-Network) breakthrough.
- EN
MetaLearning-Standford-Lecture4
Stanford CS 330 Meta-Learning lecture notes — exploring metric learning, Siamese networks, and Matching Networks for few-shot classification.
- EN
Reinforcement Learning Principle Day4
Reinforcement learning study notes — temporal difference learning: TD(0), SARSA, and Q-learning algorithms.
2020
- EN
Reinforcement Learning-Principle-Day3
Reinforcement learning study notes — Monte Carlo methods for prediction and control in model-free settings.
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HHKB's BS and Delete 按钮引起的疑惑
Debugging notes on common deletion-related confusions in programming and system administration.
- EN
MetaLearning-Standford-Lecture3
Stanford CS 330 Meta-Learning lecture notes — covering optimization-based meta-learning methods including MAML and its variants.
- EN
MetaLearning-Standford-Lecture2
Stanford CS 330 Meta-Learning lecture notes — covering learning-to-learn approaches, few-shot learning, and meta-optimization fundamentals.
- EN
Reinforcement Learning-Principle-Day2
Reinforcement learning study notes — covering dynamic programming methods: policy evaluation, policy iteration, and value iteration.
- EN
Slurm-Day5
Slurm cluster management notes — best practices for large-scale training jobs and multi-node distributed setups.
- EN
Slurm-Day4
Slurm cluster management notes — monitoring, accounting, and troubleshooting common cluster issues.
- EN
Slurm-Day3
Slurm cluster management notes — advanced job management with dependencies, priorities, and QOS configurations.