Real-Time Bidding with Side Information

Authors: arthur flajolet, Patrick Jaillet

NeurIPS 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We develop UCB-type algorithms that combine two streams of literature: the confidence-set approach to linear contextual MABs and the probabilistic bisection search method for stochastic root-finding. Under mild assumptions on the underlying unknown distribution, we establish distributionindependent regret bounds of order O(d T) when either B = or when B scales linearly with T.
Researcher Affiliation Academia Arthur Flajolet MIT, ORC flajolet@mit.edu Patrick Jaillet MIT, EECS, LIDS, ORC jaillet@mit.edu
Pseudocode Yes Algorithm 1: Interval updating procedure at the end of phase k
Open Source Code No The paper does not provide any statements about open-sourcing code or links to a code repository.
Open Datasets No The paper is theoretical and does not describe the use of any datasets for training.
Dataset Splits No The paper is theoretical and does not describe the use of any datasets or their splits for validation.
Hardware Specification No The paper is theoretical and does not mention any hardware specifications for running experiments.
Software Dependencies No The paper is theoretical and does not specify any software dependencies with version numbers for experimental reproducibility.
Experiment Setup No The paper is theoretical and does not describe a concrete experimental setup with hyperparameters or training settings.