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#GHC17
Tips and Techniques for
Hyperparameter Optimization
Alexandra Johnson | @alexandraj777 | alexandra@sigopt.com
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Example: Beating Vegas
Scott Clark. Using Model Tuning to Beat
Vegas.
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Red Box = Hyperparameter
TensorFlow Playground
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Terminology
Optimization =
tuning
Model tuning =
hyperparameter
optimization
Model selection is
related
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Tune the Whole Pipeline
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Include Feature Parameters
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Include Feature Parameters
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Choosing a Metric
Balance long-term
and short-term goals
Question underlying
assumptions
Example from
Microsoft
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Composite Metric
Example: Lifetime Value
clicks*wclicks + likes*wlikes + views*wviews
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Choose Multiple Metrics
Balance competing
metrics
Explore “efficient
frontier”
Image from PhD Comics
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Avoiding Overfitting
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Optimization Loop
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Get A Suggestion
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Split Data into k Subsamples
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Repeat for each subsample
Train
Evaluate
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Report An Observation
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Repeat for New Hyperparameters
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Optimization Methods
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Hand Tuning
Hand tuning is time
consuming and
expensive
Algorithms can
quickly and cheaply
beat expert tuning
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Grid Search Random Search Bayesian
Optimization
Alternatives to Hand Tuning
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Alternatives to Hand Tuning
Genetic algorithms
Particle-based methods
Convex optimizers
Simulated annealing
To name a few...
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
No Grid Search
Hyper-
parameters
Model
Evaluations
2 100
3 1,000
4 10,000
5 100,000
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
No Random Search
Theoretically more
effective than grid
search
Large variance in
results
No intelligence
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Bayesian Optimization
Explore/exploit
Ideal for "expensive"
optimization
No requirements on:
convexity,
differentiability,
continuity
PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017
PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17
Takeaways
Optimize the entire pipeline
Ensure generalization
Use Bayesian optimization
FEEDBACK? RATE AND REVIEW THE SESSION ON OUR MOBILE APP
Download the GHC 17 app at http://bit.ly/ghc17app or search GHC 2017 in the app store
Thank you!
alexandra@sigopt.com | @alexandraj777

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Tips and techniques for hyperparameter optimization

  • 1. #GHC17 Tips and Techniques for Hyperparameter Optimization Alexandra Johnson | @alexandraj777 | alexandra@sigopt.com
  • 2. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Example: Beating Vegas Scott Clark. Using Model Tuning to Beat Vegas.
  • 3. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Red Box = Hyperparameter TensorFlow Playground
  • 4. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Terminology Optimization = tuning Model tuning = hyperparameter optimization Model selection is related
  • 5. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Tune the Whole Pipeline
  • 6. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Include Feature Parameters
  • 7. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Include Feature Parameters
  • 8. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Choosing a Metric Balance long-term and short-term goals Question underlying assumptions Example from Microsoft
  • 9. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Composite Metric Example: Lifetime Value clicks*wclicks + likes*wlikes + views*wviews
  • 10. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Choose Multiple Metrics Balance competing metrics Explore “efficient frontier” Image from PhD Comics
  • 11. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Avoiding Overfitting
  • 12. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Optimization Loop
  • 13. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Get A Suggestion
  • 14. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Split Data into k Subsamples
  • 15. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Repeat for each subsample Train Evaluate
  • 16. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Report An Observation
  • 17. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Repeat for New Hyperparameters
  • 18. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Optimization Methods
  • 19. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Hand Tuning Hand tuning is time consuming and expensive Algorithms can quickly and cheaply beat expert tuning
  • 20. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Grid Search Random Search Bayesian Optimization Alternatives to Hand Tuning
  • 21. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Alternatives to Hand Tuning Genetic algorithms Particle-based methods Convex optimizers Simulated annealing To name a few...
  • 22. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 No Grid Search Hyper- parameters Model Evaluations 2 100 3 1,000 4 10,000 5 100,000
  • 23. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 No Random Search Theoretically more effective than grid search Large variance in results No intelligence
  • 24. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Bayesian Optimization Explore/exploit Ideal for "expensive" optimization No requirements on: convexity, differentiability, continuity
  • 25. PAGE | GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 PRESENTED BY THE ANITA BORG INSTITUTE AND THE ASSOCIATION FOR COMPUTING MACHINERY #GHC17 Takeaways Optimize the entire pipeline Ensure generalization Use Bayesian optimization
  • 26. FEEDBACK? RATE AND REVIEW THE SESSION ON OUR MOBILE APP Download the GHC 17 app at http://bit.ly/ghc17app or search GHC 2017 in the app store Thank you! alexandra@sigopt.com | @alexandraj777