Heidi Howard explores how to construct resilient distributed systems on top of unreliable components. Howard discusses which algorithms are best suited to different situations.
Alexander Lavin introduces the Numenta Anomaly Benchmark (NAB), a framework for evaluating anomaly detection algorithms on streaming data.
Martin Thompson focuses on algorithms which provide very high throughput while keeping latency low and predictable, discussing the concurrency theory and implementing these algorithms in Java 8.
Diego Ongaro introduces Raft, a consensus algorithm for managing a replicated log by separating the key elements of consensus and reducing the number of states that must be considered.
Tyler McMullen discusses how probabilistic algorithms actually work in practice and how to know they'll be safe and reliable in critical production systems.
Mini-talks: The Machine Intelligence Landscape: A Venture Capital Perspective. The future of global, trustless transactions on the largest graph: blockchain. Algorithms for Anti-Money Laundering
The authors introduce Cybertron, a new tool for reducing I/O operations in data-parallel programs through a constraint-based encoding.
ASPIRE:Exploiting Asynchronous Parallelism in Iterative Algorithms using a Relaxed Consistency-based DSM
The authors present a relaxed memory consistency model and consistency protocol that tolerate communication latency and minimize the use of stale values, outperforming other models.
Terence Parr shows the key practical advances in parsing from the last 25 years, provides algorithm comparisons, and separates the promises from reality.
Fangjin Yang, creator of Druid, shows how approximation algorithms can help system scale out linearly and process huge amount of data quickly with small memory footprint.
Aish Fenton discusses Netflix' machine learning algorithms, including distributed Neural Networks on AWS GPUs, providing insight into offline experimentation and online AB testing.
Roger Orr solves a problem with different levels of complexity trying to answer what the complexity notation actually means and why it is important in practice.