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291 posts in total. Keep on posting.
Showing posts 265–276 of 291. Each entry opens locally on this site; legacy Hexo posts link back to their original article at the bottom for reference.
2022
- 中
极路由S1-无官方破解路径下保姆级教程，辛酸刷机历程
极路由1S (5661A) 刷机保姆级教程——在没有官方破解路径的情况下，从 breed 引导刷入到 OpenWrt 的完整折腾记录。
2021
- 中
现代操作系统原理与实现-陈海波-Day 1
陈海波《现代操作系统》学习笔记——从系统调用、文件系统到内核模块，理解操作系统各组件如何协同工作。
- EN
Intel mac to M1 chip mac
A practical guide to migrating from Intel Mac to Apple M1 Silicon, covering compatibility issues, setup tips, and performance differences.
- EN
Reinforcement Learning-Principle-Day11
Reinforcement learning study notes — reward shaping, inverse RL, and imitation learning techniques.
- EN
Reinforcement Learning-Principle-Day10
Reinforcement learning study notes — exploration strategies: epsilon-greedy, UCB, Thompson sampling, and curiosity-driven methods.
- EN
MetaLearning-Standford-Lecture5
Stanford CS 330 Meta-Learning lecture notes — covering Bayesian meta-learning and neural processes for uncertainty-aware few-shot prediction.
- EN
Reinforcement Learning-Principle-Day9
Reinforcement learning study notes — multi-agent reinforcement learning, cooperative and competitive settings.
- EN
Reinforcement Learning-Principle-Day8
Reinforcement learning study notes — model-based reinforcement learning and planning with learned dynamics.
- EN
Reinforcement Learning-Principle-Day7
Reinforcement learning study notes — advanced policy optimization: PPO, TRPO, and trust region methods.
- EN
Operating System Memory Address
Notes on operating system memory management — covering virtual addressing, page tables, TLB, and memory allocation strategies.
- EN
Reinforcement Learning-Principle-Day6
Reinforcement learning study notes — policy gradient methods: REINFORCE, Actor-Critic, and A2C algorithms.
- EN
Reinforcement Learning-Principle-Day5
Reinforcement learning study notes — function approximation and the DQN (Deep Q-Network) breakthrough.