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从平均到加速,只有一个步长

From Averaging to Acceleration, There is Only a Step-size
课程网址: https://videolectures.net/videos/colt2015_flammarion_averaging_ac...  
主讲教师: Nicolas Flammarion
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2025-02-04
课程语种: 英语
中文简介:
我们证明了非强凸问题的加速梯度下降法、平均梯度下降法和重球法可以重新表述为常参数二阶差分方程算法,其中系统的稳定性等价于以速率O(1/n^2)收敛,其中n为迭代次数。我们提供了相应的线性动力系统的特征值的详细分析,显示了各种振荡和非振荡行为,以及具有显式常数的尖锐稳定性结果。我们还考虑了噪声梯度可用的情况,在那里我们扩展了我们的一般收敛结果,这提出了一种替代算法(即,具有不同的步长),它显示了平均和加速的良好方面。
课程简介: We show that accelerated gradient descent, averaged gradient descent and the heavy-ball method for non-strongly convex problems may be reformulated as constant parameter second-order difference equation algorithms, where stability of the system is equivalent to convergence at rate O(1/n^2) where n is the number of iterations. We provide a detailed analysis of the eigenvalues of the corresponding linear dynamical system, showing various oscillatory and non-oscillatory behaviors, together with a sharp stability result with explicit constants. We also consider the situation where noisy gradients are available, where we extend our general convergence result, which suggest an alternative algorithm (i.e., with different step sizes) that exhibits the good aspects of both averaging and acceleration.
关 键 词: 非强凸问题; 平均梯度下降法; 重球法
课程来源: 视频讲座网
数据采集: 2025-03-30:zsp
最后编审: 2025-03-30:zsp
阅读次数: 3