We develop a new active learning algorithm for the streaming setting satisfying three important properties: 1) It provably works for any classifier representation and classification problem including those with severe noise. 2) It is efficiently implementable with an ERM oracle. 3) It is more aggressive than all previous approaches satisfying …
Network models provide a unifying framework for understanding dependencies among variables in medical, biological, and other sciences. Networks can be used to reveal underlying data structures, infer functional modules, and facilitate experiment design. In practice, however, size, uncertainty and complexity of the underlying associations render these applications challenging. In this …
The recent investment in neurotechnology development has spurred tremendous excitement about the potential to uncover the operating principles of biological neural circuits. However, a storm is brewing. If the neuroengineering community is able to achieve their goals of developing technologies that increase the number of interfaced neurons by orders of …
Quasi-Newton methods are viable alternatives to Newton’s method for solving optimization problems because they do not require computing and solving with the potentially very large Hessian matrix while still maintaining a superlinear convergence rate. Systems of linear equations arising from quasi-Newton methods can be solved efficiently using the compact representation …
Optimizing the k-means objective with Lloyd’s algorithm is a classic strategy to separate a set of datapoint into individual clusters. More recent data in biology and social networks necessitates overlapping clustering. I’ll present a generalization of the k-means objective function that incorporates overlapping partitions as well as outlier detection. A …
The notion of machines that can learn has caught imaginations since the days of the early computer. In recent years, as we face burgeoning amounts of data around us that no human mind can process, machines that can learn to automatically find insights from such vast amounts of data have …
Selecting the teams for the College Football Playoff for NCAA Division IA men’s football is a controversial process performed by the selection committee. We present a method for forecasting the four team playoff weeks before the selection committee makes this decision. Our method uses a modified logistic regression/Markov chain model …