Discusses design considerations for computing and storage in edge IoT sensor architectures, emphasizing hardware components and energy optimization techniques.
Covers optimization techniques in machine learning, focusing on convexity, algorithms, and their applications in ensuring efficient convergence to global minima.
Discusses optimization techniques in machine learning, focusing on stochastic gradient descent and its applications in constrained and non-convex problems.
