In this course, you’ll learn theoretical foundations of optimization methods used for training deep machine learning models. Why does gradient descent work? Specifically, what can we guarantee about ...

The result is lighter, stiffer structures and the potential for subsystem integration through multifunctional materials. Optimization for Tailored Fiber Placement (TFP) Composites A gradient-based ...

The Rosenbrock function, also referred to as the Valley or Banana function, is a popular test problem for gradient-based optimization algorithms. It is shown in the plot above in its two-dimensional ...

Neel, Seth, Aaron Leon Roth, and Saeed Sharifi-Malvajerdi. "Descent-to-Delete: Gradient-Based Methods for Machine Unlearning." Paper presented at the 32nd Algorithmic Learning Theory Conference, March ...

Topics covered range from automatic code generation, graphical models, and gradient-based algorithms for signal recovery, to semidefinite programming (SDP) relaxation and radar waveform design via SDP ...

The balancing act between the influences of transcription factors acting as activators and repressors appears to be consistent with other gradient-based signaling cascades, such as that for Hh in ...