Learning a unified embedding for visual search at Pinterest

Learning a unified embedding for visual search at Pinterest Zhai et al., KDD'19 Last time out we looked at some great lessons from Airbnb as they introduced deep learning into their search system. Today’s paper choice highlights an organisation that has been deploying multiple deep learning models in search (visual search) for a while: Pinterest. … Continue reading Learning a unified embedding for visual search at Pinterest

Applying deep learning to Airbnb search

Applying deep learning to Airbnb search Haldar et al., KDD'19 Last time out we looked at Booking.com’s lessons learned from introducing machine learning to their product stack. Today’s paper takes a look at what happened in Airbnb when they moved from standard machine learning approaches to deep learning. It’s written in a very approachable style … Continue reading Applying deep learning to Airbnb search

Beyond data and model parallelism for deep neural networks

Beyond data and model parallelism for deep neural networks Jia et al., SysML'2019 I’m guessing the authors of this paper were spared some of the XML excesses of the late nineties and early noughties, since they have no qualms putting SOAP at the core of their work! To me that means the "simple" object access … Continue reading Beyond data and model parallelism for deep neural networks

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

GAN dissection: visualizing and understanding generative adversarial networks

GAN dissection: visualizing and understanding generative adversarial networks Bau et al., arXiv'18 Earlier this week we looked at visualisations to aid understanding and interpretation of RNNs, today’s paper choice gives us a fascinating look at what happens inside a GAN (generative adversarial network). In addition to the paper, the code is available on GitHub and … Continue reading GAN dissection: visualizing and understanding generative adversarial networks

Understanding hidden memories of recurrent neural networks

Understanding hidden memories of recurrent neural networks Ming et al., VAST’17 Last week we looked at CORALS, winner of round 9 of the Yelp dataset challenge. Today’s paper choice was a winner in round 10. We’re used to visualisations of CNNs, which give interpretations of what is being learned in the hidden layers. But the … Continue reading Understanding hidden memories of recurrent neural networks