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Efficient Nonmyopic Batch Active Search Shali Jiang Gustavo Malkomes Matthew Abbott Benjamin Moseley Roman Garnett NeurIPS 2018 1 Many real problems involve searching for valuable items from a large pool of candidates in an iterative

  1. Efficient Nonmyopic Batch Active Search Shali Jiang Gustavo Malkomes Matthew Abbott Benjamin Moseley Roman Garnett NeurIPS 2018 1

  2. Many real problems involve searching for valuable items from a large pool of candidates in an iterative fashion Drug discovery Materials discovery 2

  3. What is active search 3

  4. What is active search 3

  5. What is active search inference model ( gives probabilities ) Pr( ) 3

  6. What is active search select a point inference model ( gives probabilities ) Pr( ) 3

  7. What is active search select a point Is it positive? inference model ( gives probabilities ) Pr( ) Oracle 3

  8. What is active search select a point Is it positive? inference model ( gives probabilities ) Pr( ) Oracle yes/no 3

  9. What is active search select a point Is it positive? inference model ( gives probabilities ) Pr( ) Oracle yes/no 3

  10. What is active search select a point Is it positive? inference model ( gives probabilities ) Pr( ) Oracle yes/no 3

  11. What is active search select a point Is it positive? inference model ( gives probabilities ) Pr( ) Oracle yes/no 3

  12. What is active search select a point Is it positive? inference model ( gives probabilities ) Identify as many Pr( ) positives as possible in a given number of queries. Oracle yes/no 3

  13. What is active search How? select a point Is it positive? inference model ( gives probabilities ) Identify as many Pr( ) positives as possible in a given number of queries. Oracle yes/no 3

  14. What is active search How? select a batch of points Is it positive? inference model ( gives probabilities ) Identify as many Pr( ) positives as possible in a given number of queries. Oracle yes/no 3

  15. The most straightforward policy one might think of is greedy: —always choose the points with highest probabilities 4

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The most straightforward policy one might think of is greedy: —always choose the points with highest probabilities X ∗ = arg max “expected #positives in X ” X 4

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