ESE

When it comes to security, hardware is the new software. Starting some years ago, this shift was made plain when a litany of attacks, such as "Spectre/Meltdown" and "Rowhammer", shattered our confidence in processors as a root of trust. Making matters worse, modern processors are incredibly complex, and have (as it turns out) been designed […]

Latent variable models have been an integral part of probabilistic machine learning, ranging from simple mixture models to variational autoencoders to powerful diffusion probabilistic models at the center of recent media attention. Perhaps less well-appreciated is the intimate connection between latent variable models and data compression, and the potential of these models for advancing natural […]

We consider the problem of network utility maximization (NUM) and propose a new Learning-NUM framework,  where the users’ utility functions are unknown apriori and the utility function values can be observed only after the corresponding traffic is delivered to the destination.   We start by considering linear utility functions and propose a priority-based network control policy, […]

For the past two decades, power management and delivery has been a bottleneck, limiting the size and performance of a range of applications from performance computing to mobile phones and wearables. In the coming decades, power electronics will become the ‘glue’ of the modern energy system network. With electronics embedded deeply into this network, well […]