https://terms-en.ai-term-hub.com/zh/tags/kernels/Recent content in Kernels on 中文AI术语词典Hugozh-cnSat, 18 Jul 2026 11:44:45 +0000https://terms-en.ai-term-hub.com/zh/terms/bayesian_interpretation_of_kernel_regularization/Sat, 18 Jul 2026 11:08:51 +0000https://terms-en.ai-term-hub.com/zh/terms/bayesian_interpretation_of_kernel_regularization/<h2 id="definition">Definition</h2> <p>这一概念确立了：使用特定核函数最小化正则化风险泛函，等价于在贝叶斯框架中寻找最大后验概率（MAP）估计。具体来说，它揭示了确定性核方法与概率性高斯过程之间的深层联系。</p> <h3 id="summary">Summary</h3> <p>一个理论框架，将支持向量机等核方法与高斯过程在贝叶斯先验假设下联系起来。</p> <h2 id="key-concepts">Key Concepts</h2> <ul> <li>高斯过程</li> <li>最大后验估计</li> <li>正则化作为先验</li> <li>核方法</li> </ul> <h2 id="use-cases">Use Cases</h2> <ul> <li>理解支持向量机的理论基础</li> <li>将高斯过程技术应用于核回归</li> <li>为确定性模型推导不确定性估计</li> </ul> <h2 id="related-terms">Related Terms</h2> <ul> <li><a href="https://terms-en.ai-term-hub.com/en/terms/gaussian_processes-%E9%AB%98%E6%96%AF%E8%BF%87%E7%A8%8B/">gaussian_processes (高斯过程)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/support_vector_machines-%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/">support_vector_machines (支持向量机)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/regularization-%E6%AD%A3%E5%88%99%E5%8C%96/">regularization (正则化)</a></li> <li><a href="https://terms-en.ai-term-hub.com/en/terms/prior_distribution-%E5%85%88%E9%AA%8C%E5%88%86%E5%B8%83/">prior_distribution (先验分布)</a></li> </ul>