Keeping CALM: when distributed consistency is easy Hellerstein & Alvaro, arXiv 2019 The CALM conjecture (and later theorem) was first introduced to the world in a 2010 keynote talk at PODS. Behind its simple formulation there’s a deep lesson to be learned with the power to create ripples through our industry akin to the influence … Continue reading Keeping CALM: when distributed consistency is easy
Month: March 2019
Efficient large-scale fleet management via multi-agent deep reinforcement learning
Efficient large-scale fleet management via multi-agent deep reinforcement learning Lin et al., KDD'18 A couple of weeks ago we looked at a survey paper covering approaches to dynamic, stochastic, vehicle routing problems (DSVRPs). At the end of the write-up I mentioned that I couldn’t help wondering about an end-to-end deep learning based approach to learning … Continue reading Efficient large-scale fleet management via multi-agent deep reinforcement learning
Large scale GAN training for high fidelity natural image synthesis
Large scale GAN training for high fidelity natural image synthesis Brock et al., ICLR'19 Ian Goodfellow’s tweets showing x years of progress on GAN image generation really bring home how fast things are improving. For example, here’s 4.5 years worth of progress on face generation: And here we have just two years of progress on … Continue reading Large scale GAN training for high fidelity natural image synthesis
the morning paper 