Abstract: The framework of integral quadratic constraints is used to perform an analysis of gradient descent with varying step sizes. Two performance metrics are considered: convergence rate and noise ...
Abstract: The gradient descent bit-flipping with momentum (GDBF-w/M) and probabilistic GDBF-w/M (PGDBF-w/M) algorithms significantly improve the decoding performance of the bit-flipping (BF) algorithm ...
You heard it here first! The new Otis solver in Houdini 21 uses Vertex Block Descent! They made some nice improvements for stability, including several new hessian approximations. It also runs in ...
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Linear regression gradient descent explained simply
Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
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