The Epoch-Greedy Algorithm for Contextual Multi-armed Bandits

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Creating a Hypotheses (Cont.)

• Want to be within ε of the threshold

– Need ≈ O(1/ε)

• As the function gets more complex

– Need ≈ O((1/ε)*C)

– C denotes how complex the function is

– A quick note for those of you who took 156 the C

is similar to VC dimension

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Creating a Hypotheses (Cont.) • Want to be within ε of the threshold – Need ≈ O(1/ε) • As the function gets more complex – Need ≈ O((1/ε)*C) – C denotes how complex the function is – A quick note for those of you who took 156 the C is similar to VC dimension

Epoch • Don’t always know the time horizon • Append groupings of known time horizons – Repeat until time actually ends • This specific paper has chosen a single exploration step at the beginning of each epoch

Page 1 and 2: The Epoch-Greedy Algorithm for Cont
Page 3 and 4: Overview • Bandit problem • Con
Page 5 and 6: Web Example • Some number of ads
Page 7 and 8: Contextual Bandits • Add Context
Page 9 and 10: Overview • Bandit problem • Con
Page 11 and 12: Exploration • Look at a fixed tim
Page 13: Creating a Hypotheses • Simple tw
Page 17 and 18: Review Using Web Example • Have a
Page 19: Review (Cont.) • Search Query - H

The Epoch-Greedy Algorithm for Contextual Multi-armed Bandits

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