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02/14/2020
Multi-variate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Time series forecasting is often fundamental to scientific and engineeri...
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08/02/2019
A Hierarchical Bayesian Model for Size Recommendation in Fashion
We introduce a hierarchical Bayesian approach to tackle the challenging ...
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07/23/2019
A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce
Personalized size and fit recommendations bear crucial significance for ...
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02/10/2019
A Bandit Framework for Optimal Selection of Reinforcement Learning Agents
Deep Reinforcement Learning has been shown to be very successful in comp...
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12/04/2017
Stochastic Maximum Likelihood Optimization via Hypernetworks
This work explores maximum likelihood optimization of neural networks th...
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06/28/2015
Neural Simpletrons - Minimalistic Directed Generative Networks for Learning with Few Labels
Classifiers for the semi-supervised setting often combine strong supervi...
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11/15/2012
A Truncated EM Approach for Spike-and-Slab Sparse Coding
We study inference and learning based on a sparse coding model with `spi...
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05/12/2011