Results 31 to 40 of about 492,986 (210)
Resourceful Contextual Bandits
CoRR, 2014 This is the full version of a paper in COLT 2014. Version history: (v2) Added some details to one of the proofs, (v3) a big revision following comments from COLT reviewers (but no new results), (v4) edits in related work, minor edits elsewhere. (v6) A correction for Theorem 3, corollary for contextual dynamic pricing with discretization; updated follow-
Ashwinkumar Badanidiyuru +2 more
openaire +3 more sources
CoRR, 2019 Contextual Bandits is one of the widely popular techniques used in applications such as personalization, recommendation systems, mobile health, causal marketing etc . As a dynamic approach, it can be more efficient than standard A/B testing in minimizing regret.
Praneet Dutta +3 more
openaire +2 more sources
Adapting to Misspecification in Contextual Bandits
CoRR, 2021 Appeared at NeurIPS ...
Dylan J. Foster +3 more
openaire +4 more sources
Semiparametric Contextual Bandits
CoRR, 2018 This paper studies semiparametric contextual bandits, a generalization of the linear stochastic bandit problem where the reward for an action is modeled as a linear function of known action features confounded by an non-linear action-independent term. We design new algorithms that achieve $\tilde{O}(d\sqrt{T})$ regret over $T$ rounds, when the linear ...
Akshay Krishnamurthy +2 more
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Network, 2022 5G networks have been experiencing challenges in handling the heterogeneity and influx of user requests brought upon by the constant emergence of various services.
Ralph Voltaire J. Dayot +2 more
doaj +1 more source
Post-Contextual-Bandit Inference
Advances in neural information processing systems, 2021 Contextual bandit algorithms are increasingly replacing non-adaptive A/B tests in e-commerce, healthcare, and policymaking because they can both improve outcomes for study participants and increase the chance of identifying good or even best policies.
Bibaut, Aurélien +4 more
openaire +7 more sources
, 2021 Data used in real world-inspired experiments for submission titled "Causal Contextual Bandits with Targeted Interventions"
Anonymous
core +1 more source
Contextual Bandit with Missing Rewards
CoRR, 2020 We consider a novel variant of the contextual bandit problem (i.e., the multi-armed bandit with side-information, or context, available to a decision-maker) where the reward associated with each context-based decision may not always be observed("missing rewards").
Djallel Bouneffouf 0001 +2 more
openaire +3 more sources
Practical Contextual Bandits with Feedback Graphs
, 2023 While contextual bandit has a mature theory, effectively leveraging different feedback patterns to enhance the pace of learning remains unclear. Bandits with feedback graphs, which interpolates between the full information and bandit regimes, provides a ...
Zhang, Mengxiao +4 more
core +1 more source