The authors investigate the interrelationships between macro-systems of governments and financial institutions by studying the dynamic propagation mechanisms of macroeconomic shocks.
Using ant colonies and beehives as a starting point, this presentation examines a handful of natural and computer systems to illustrate how to cast system-wide problems into solutions at the individual component level, yielding incredibly simple algorithms for incredibly complex collective behaviors.
A presentation on fundamental questions in algorithmic data science, a discipline at the border of computer science and statistics.
Cook, Two Sigma’s open-source resource scheduler for compute clusters, uses preemption to achieve low latency and high throughput.
Sixty-five percent of respondents worry about the loss of G3 central bank credibility, defined as the ability of those banks to influence economic growth and market prices.
Data on highly skilled (H-1B) foreign workers suggests that wage pressure in the US may be coming from the bottom end of the distribution more than the top.
A Two Sigma research scientist provides an overview of some of the most interesting research presented at ICML 2016.
ABRA is a suite of algorithms to compute and maintain probabilistically-guaranteed, high-quality, approximations of the betweenness centrality of all nodes (or edges) on both static and fully dynamic graphs.
The authors lay out the fundamental concepts behind OCR--a new runtime system designed to meet the needs of extreme-scale computing--and compare OCR performance to that from MPI for two simple benchmarks.
The ABRA suite of algorithms computes and maintains high-quality approximations of the betweenness centrality of all nodes or edges on static and fully dynamic graphs.