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Robust Budget Pacing with a Single Sample

ICML 2023 · Bandits and online learning › Online convex optimization and games · approach: Learning for pricing and auctions · 0 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Dual FTRL with target rate estimated from one sample per distribution (instead of T log T samples)budget pacing / online allocation with time-varying distributions · theoretical regret analysis, Wasserstein-shifted sampling distributionsregretHelped
Learning the empirical optimal dual and directly bidding with it (Algorithm 1) instead of tracking a target via Dual FTRL (ablation)dual-based bidding with one sample per distribution · Example with Wasserstein-shifted sampling distributions (W ≤ 3ε)regretHurt
Using Dual FTRL to track the empirical target consumption sequence instead of the naive dual priceDual FTRL budget pacing · theoretical regret with sum of Wasserstein distancesregretHelped

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