In this paper, we study robust algorithms for the experts problem under memory constraints.

ASPEN also achieves high resource utilization and memory reuse by letting each resource asynchronously traverse depthwise in the DNN graph to its full computing potential.

In large-scale applications, datasets often contain billions of high-dimensional points. Grouping similar data points into clusters is crucial for understanding and organizing datasets.

Effective resistances have a broad range of algorithmic implications.

We develop a deeper understanding of its relationship with more conventional analyses of extragradient methods [Nem04, Nes07]. We also give improved solvers for the subproblems required by variants of the [She17] algorithm, designed through the lens of relative smoothness [BBT17, LFN18].