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KDD 2017

GDP Labs
October 25, 2017

KDD 2017

GDP Labs

October 25, 2017
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  1. KDD 2017
    Oey, Michael Julio
    Gregorius Edwadr

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  2. KDD
    ● Held by Special Interest Group on Knowledge Discovery and Data
    Mining ( SIGKDD )
    ● Part of Association for Computing Machinery ( ACM )
    ● SIGKDD has become an official ACM SIG since 1998
    ● ACM SIGKDD has hosted an annual conference since 1995
    ● Considered as the most influential forum for knowledge discovery and
    data mining research
    GDP Labs Confidential

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  3. KDD
    2012
    Beijing
    2013
    Chicago
    2014
    New York
    2015
    Sydney
    2016
    San Fransisco
    2017
    Halifax
    GDP Labs Confidential

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  4. KDD 2017
    ● Held at Halifax, Canada
    ● August 13th - 17th 2017
    ● Consists of :
    ○ Tutorial
    ○ Workshop
    ○ Main Conference
    ■ Keynote
    ■ Paper presentations
    ● Sponsored by a lot of named tech companies
    from around the world
    GDP Labs Confidential

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  5. KDD 2017
    ● From Theory to Data Product - Applying Data Science Methods to Effect
    Business Change
    ● A/B Testing at Scale : Accelerating Software Innovation
    ● Workshop on Causal Discovery
    ● Anomaly Detection in Finance
    ● Platforms and Infrastructure
    ● Applied Machine Learning
    ● Deep Learning
    ● Intelligent Systems and Data Science
    ● KDD Panel : The Future of Artificially Intelligent Assistants
    ● Clustering
    ● Web Applications
    GDP Labs Confidential

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  6. From Theory to
    Data Product :
    Applying Data
    Science Methods
    to Effect Business
    Change
    ● Advanced analytic entry points
    ○ The Technology Directive
    ○ The Field of Dreams
    ○ The Ambitious Executive
    ○ The Smart Competitor
    ● Are you asking the right questions?
    ○ Business valuable questions
    ● Agile Approach to Data Driven
    Decision Making
    ○ What is agile?
    ○ Managing uncertainty
    ● Data science is expensive, but if you
    don’t do it, you will be left behind
    Danielle Leighton
    Lindsay Brin
    Janet Forbes
    T4G Limited
    GDP Labs Confidential

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  7. Google Vizier - A
    Service for Black
    Box Optimization
    Daniel Golovin
    Google Research
    ● Used on many applications
    ○ A/B Testing
    ○ Machine Learning
    ○ Physical Design
    ○ Robotics
    ● Vizier
    ○ Easy to use
    ○ Reliable
    ○ Scalable
    ○ Flexible
    ○ State of the art
    ● They tried Vizier to bake chocolate
    chip cookies
    GDP Labs Confidential

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  8. TFX : TensorFlow
    Extended - A
    Production Scale
    ML Platform
    Heng Tze Cheng
    Google Research
    ● Productionizing ML pipeline is hard
    ● End to end ( from data to serving )
    ● Design principles :
    ○ One ML platform for many
    products
    ○ Continuous training and serving
    ○ Human in the loop
    ○ Reliable and scalable
    ● Steps :
    ○ Data analysis
    ○ Data validation
    ○ Data transformation
    ○ Trainer
    ○ Model validation & evaluation
    ○ Serving
    ● Documentation -> passive way
    ● Education -> active way ( teach, talk )
    ● Automation -> key principles
    GDP Labs Confidential

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  9. Designing AI at
    Scale to Power
    Everyday Life
    Rajesh Parekh
    Facebook
    ● Data drives all product at Facebook
    ● FB Learner Flow
    ○ Help non ML people to use ML
    ○ 70% users are non AI-experts
    ○ 25% engineers are active users
    ● Applied Machine Learning at Facebook
    ○ Computer Vision
    ○ Deep Text
    ○ Speech and Video
    ○ AI Powered Camera
    ● What’s next
    ○ Multi modal learning
    ○ Transfer learning
    ○ Multi lingual modeling
    ○ Weakly supervised /
    unsupervised learning
    GDP Labs Confidential

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  10. Industrial Machine
    Learning
    Josh Bloom
    General Electric
    ● Data produced by machines will
    overcome data produced by people
    ● Industrial Machine Learning
    ○ Preventive Maintenance
    ○ Anomaly / Failure detection
    ○ Etc
    ● Industrial level is more dangerous than
    social level
    ● Optimization metric
    ○ Higher accuracy != higher value
    ○ Drive towards higher
    precision/low FPR
    ● Models
    ○ Physical model
    ○ Data driven model
    ● Interpretability and accuracy trade off
    ● Small improvement helps a lot
    ● Hard to convince everyone to
    transition
    GDP Labs Confidential

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  11. KDD 2017
    ● Deep Learning for Personalized Search and Recommender Systems
    ● Recent Advances in Feature Selection: A Data Perspective
    ● 2017 Edition of AdKDD and TargetAd
    ● Three Principles of Data Science: Predictability, Stability, and
    Computability
    ● Supervised Learning
    ● Deep Learning
    ● Intelligent Systems and Data Science
    ● Hands-On Tutorial Declarative, Large-Scale Machine Learning with
    Apache SystemML
    ● Hands-On Tutorial Tensor Flow
    GDP Labs Confidential

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  12. Online Advertising
    GDP Labs Confidential

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  13. How ad works
    GDP Labs Confidential

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  14. How ad works
    GDP Labs Confidential

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  15. How ad works
    GDP Labs Confidential

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  16. How ad works
    Advertiser
    Publisher
    GDP Labs Confidential

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  17. Ad Pricing
    ● Popular Model
    ○ CPM -> cost per mille impression
    ○ CPC -> cost per click
    ○ CPA -> cost per acquisition
    ● Others
    ○ CPF -> cost per follower
    ○ CPV -> cost per view
    ○ CPI -> cost per install
    ○ CPD -> cost per download
    GDP Labs Confidential

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  18. Criteo
    GDP Labs Confidential

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  19. Criteo
    GDP Labs Confidential

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  20. Attribution Model
    GDP Labs Confidential

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  21. Attribution Probability
    GDP Labs Confidential

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  22. Attribution Aware Bidder
    GDP Labs Confidential

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  23. Bidding
    GDP Labs Confidential

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  24. Result
    GDP Labs Confidential

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