Aaron Roth, Associate Professor, University of Pennsylvania
The Algorithmic Foundations of Differential Privacy
The Reusable Holdout: Preserving Validity in Adaptive Data Analysis
Alexandra Johnson, Software Engineer, SigOpt
Intro
Ian Dewancker. SigOpt for ML: TensorFlow ConvNets on a Budget with Bayesian Optimization
Ian Dewancker. SigOpt for ML: Unsupervised Learning with Even Less Supervision Using Bayesian Optimization
Ian Dewancker. SigOpt for ML: Bayesian Optimization for Collaborative Filtering with MLlib
#1 Trusting the Defaults
Keras recurrent layers documentation
#2 Using the Wrong Metric
Ron Kohavi et al. Trustworthy Online Controlled Experiments: Five Puzzling Outcomes Explained
Xavier Amatriain. 10 Lessons Learning from Building ML Systems (Video at 19:03)
Image from PhD Comics.
See also: SigOpt in Depth: Intro to Multicriteria Optimization
#4 Too Few Hyperparameters
Image from TensorFlow Playground
Ian Dewancker. SigOpt for ML: Unsupervised Learning with Even Less Supervision Using Bayesian Optimization
#5 Hand Tuning
On algorithms beating experts: Scott Clark, Ian Dewancker and Sathish Nagappan. Deep Neural Network Optimization with SigOpt and Nervana Cloud
#6 Grid Search
Nogridsearch.com
#7 Random Search
James Bergstra and Yoshua Bengio. Random Search for Hyper-parameter Optimization
Ian Dewancker, Michael McCourt, Scott Clark, Patrick Hayes, Alexandra Johnson, George Ke. A Stratified Analysis of Bayesian Optimization Methods
Learn More
Blog.sigopt.com
sigopt.com/research
Byron Galbraith, Chief Data Scientist, Talla
https://github.com/bgalbraith/bandits
Corinna Cortes, Head of Research, Google
https://arxiv.org/pdf/1611.00068.pdf
http://www.kdd.org/kdd2016/papers/files/Paper_1069.pdf
Erik Bernhardsson, CTO, Better Mortgage
https://github.com/spotify/annoy
https://github.com/erikbern/ann-benchmarks
https://github.com/erikbern/ann-presentation
https://erikbern.com/
Layla El Asri, Research Scientist, Maluuba
Improving Scalability of Reinforcement Learning by Separation of Concerns
Towards Information-Seeking Agents
Frames: A Corpus For Adding Memory To Goal-Oriented Dialogue Systems