A major goal in systems biology is a comprehensive description of the entirety of all complex
interactions between different types of biomolecules—also referred to as the interactome …

Federated learning poses new statistical and systems challenges in training machine
learning models over distributed networks of devices. In this work, we show that multi-task …

This paper provides a review and commentary on the past, present, and future of numerical
optimization algorithms in the context of machine learning applications. Through case …

The construction of a meaningful graph topology plays a crucial role in the effective
representation, processing, analysis, and visualization of structured data. When a natural …

A major goal of neuroimaging studies is to develop predictive models to analyze the
relationship between whole brain functional connectivity patterns and behavioural traits …

The construction of a meaningful graph plays a crucial role in the success of many graph-
based representations and algorithms for handling structured data, especially in the …

A new edition of this popular text on robust statistics, thoroughly updated to include new and
improved methods and focus on implementation of methodology using the increasingly …

What do auto-encoders learn about the underlying data-generating distribution? Recent
work suggests that some auto-encoder variants do a good job of capturing the local manifold …

We generalize Newton-type methods for minimizing smooth functions to handle a sum of two
convex functions: a smooth function and a nonsmooth function with a simple proximal …