- ASAP: Fast, Approximate, Graph Pattern Mining at Scale (Usenix) -- we present A Swift Approximate Pattern-miner (ASAP), a system that enables both fast and scalable pattern mining. ASAP is motivated by one key observation: in many pattern mining tasks, it is often not necessary to output the exact answer [...] an approximate count is good enough. (via Morning Paper)
- Binci -- tackling the same problem space as Docker Compose, but aimed at ephemeral containers rather than long-running ones (e.g., for test/CI systems).
- Metrics for Investors (Andrew Chen) -- detailed take on the metrics through which investors view SaaS businesses.
- How to Fit Large Neural Networks on the Edge -- This blog explores a few techniques that can be used to fit neural networks in memory-constrained settings. Different techniques are used for the “training” and “inference” stages, and hence they are discussed separately.
Article image: Four short links