Open-source software has been a critical enabler for tremendous innovation in the software ecosystem over the past two decades. Inspired by this success, open-source hardware involves making the high-level description of hardware components freely available for others to study, change, distribute, and ultimately use in fabricating their own hardware components. Unfortunately, open-source hardware has had […]

Overparameterized neural networks have proved to be remarkably successful in many complex tasks such as image classification and deep reinforcement learning. In this talk, we will consider the role of explicit regularization in training overparameterized neural networks. Specifically, we consider ReLU networks and show that the landscape of commonly used regularized loss functions have the […]

The strong lottery ticket hypothesis (LTH) postulates that any neural network can be approximated by simply pruning a sufficiently larger network of random weights. Recent work establishes that the strong LTH is true if the random network to be pruned is a large poly-factor wider than the target one. This polynomial over-parameterization is at odds with […]