Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.
Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.
Explores the marriage problem, modeling the process as a controlled stochastic process with dynamic programming algorithms to find the optimal policy for accepting bachelors.
