Consider the following classical network design model. There are n clients in a multi-graph with a single sink node. Each edge has a cost to buy, and a length if bought; typically, costlier edges have smaller lengths. There ...

Snow coverage is often predicted through analysis of satellite images. Two of the most common satellites used for predictions are MODIS and Landsat. Unfortunately, snow coverage predictions are limited either by MODIS ...

In of optimal control and reinforcement learning, the difference in the performance of a state-of-the-art policy and a mediocre one is minuscule in comparison to their difference in amortized computational cost. Further, ...

In this thesis, we deal with two problems on multidimensional allocation, specifically in apportionment and in bin packing. The apportionment problem models the allocation of seats in a House of Representatives such that ...

Data science has provided unprecedented opportunities to learn new insights and to predict, recommend, cluster, classify, transform, and optimize. Catalyzed by large-scale, networked computer systems, vast availability of ...

Min-max optimization is a classic problem with applications in constrained optimization, robust optimization, and game theory. This dissertation covers new convergence rate results in min-max optimization. We show that the ...

Roboticists have long envisioned fully-automated robots that can operate reliably in unstructured environments. This is an exciting but extremely difficult problem; in order to succeed, robots must reason about sequential ...