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Coordinate Descent with Bandit Sampling

NeurIPS 2018 · Bandits and online learning › Multi-armed bandits · approach: Optimal stochastic bandit algorithms · 7 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
select the coordinate with the largest marginal-decrease lower boundcoordinate descent (max_r) · aloi / Lassotime to sub-optimality gap exp(-5) (seconds): 27.8 -> 6.2Helped
select the coordinate with the largest marginal-decrease lower boundcoordinate descent (max_r) · a9a / logistic regressiontime to sub-optimality gap exp(-5) (seconds): 11.8 -> 4.5Helped
select the coordinate with the largest marginal-decrease lower boundcoordinate descent (max_r) · usps / ridge regressiontime to sub-optimality gap exp(-5) (seconds): 1 -> 9.5Hurt
use bandit estimates with periodic full-coordinate refresh and explorationcoordinate descent (B_max_r) · aloi / Lassotime to sub-optimality gap exp(-5) (seconds): 27.8 -> 11Helped
use bandit estimates with periodic full-coordinate refresh and explorationcoordinate descent (B_max_r) · a9a / logistic regressiontime to sub-optimality gap exp(-5) (seconds): 11.8 -> 1.9Helped
use bandit estimates with periodic full-coordinate refresh and explorationcoordinate descent (B_max_r) · usps / ridge regressiontime to sub-optimality gap exp(-5) (seconds): 1 -> 1No clear effect
use B_max_r instead of max_rcoordinate descent · aloi / Lassotime to sub-optimality gap exp(-5) (seconds): 6.2 -> 11Hurt
use B_max_r instead of max_rcoordinate descent · a9a / logistic regressiontime to sub-optimality gap exp(-5) (seconds): 4.5 -> 1.9Helped
use B_max_r instead of max_rcoordinate descent · usps / ridge regressiontime to sub-optimality gap exp(-5) (seconds): 9.5 -> 1Helped
increase the bin size EB_max_r on a9a / logistic regression · a9a / logistic regressioniterations to log-suboptimality gap -5Hurt
increase the exploration parameter εB_max_r on a9a / logistic regression · a9a / logistic regressioniterations to log-suboptimality gap -5Hurt

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