NIPS 2012 Trends
Rather than a laundry list of papers, I thought I would comment on some trends that I observed at NIPS this year. Deep Learning is BackFor the true faithful deep learning never left, but for everybody else several recent developments have coalesced in their favor. First, data sets have gotten bigger. Bigger data sets mean more complex model families can be considered without overfitting. Once data
Deep Learning 2012 – Machine Learning (Theory)
2012 was a tumultuous year for me, but it was undeniably a great year for deep learning efforts. Signs of this include: Winning a Kaggle competition. Wide adoption of deep learning for speech recognition. Significant industry support. Gains in image recognition. This is a rare event in research: a significant capability breakout. Congratulations are definitely in order for those who managed to ach
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SLI | Classes / CS274b: Learning in Graphical Models
