MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm

Zhang, Wei; Kitts, Brendan; Han, Yanjun; Zhou, Zhengyuan; Mao, Tingyu; He, Hao; Pan, Shilie; Flores, Aaron; Gultekin, San; Weissman, Tsachy

doi:10.1145/3447548.3467113

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…For example, Gligorijevic et al (2020) uses models based on Factorization Machines to estimate the bid shading factor (i.e., the ratio of the minimum winning price to the original bid price). Secondly, distribution estimators are built using bid landscape forecasting to predict the winning probability distribution (Cui et al 2011;Ren et al 2019;Wu, Yeh, and Chen 2018;Ghosh et al 2019), and then the optimal bid is determined by searching for maximum expected surplus (Pan et al 2020;Zhou et al 2021). These estimators all admit an efficient search for optimal bid but differ in the assumption of the distribution families, such as gamma and lognormal distribution.…”

Section: Additional Related Workmentioning

confidence: 99%

“…These estimators all admit an efficient search for optimal bid but differ in the assumption of the distribution families, such as gamma and lognormal distribution. Thirdly, instead of point and distribution estimations, Zhang et al (2021) uses online learning to design nonparametric bid shading algorithms. Outside of bid shading in first-price auction, our work is also related to the work by Nedelec, El Karoui, and Perchet (2019), which designs learning-based shading strategies to do manipulation in incentive compatible though prior-dependent revenue-maximizing auctions.…”

Section: Additional Related Workmentioning

confidence: 99%

“…As far as we know, a line of works (Zhou et al 2021;Pan et al 2020) which optimizes bid shading in open firstprice auctions relies on relatively strong hypothesis about the feedback distribution W . To be specific, these studies can be summarized into a two-stage solution framework.…”

Section: Comparison With Related Work In Bid Shadingmentioning

confidence: 99%

“…Concretely, a lower bid is more likely to lose but charged less when obtaining the impression, while a higher bid is more likely to win but charged more when winning the impression. Most studies on bid shading (Pan et al 2020;Zhou et al 2021) rely heavily on the exact estimation of winning probability, but Zhang…”

Section: Introductionmentioning

confidence: 99%

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Simultaneous Optimization of Bid Shading and Internal Auction for Demand-Side Platforms

Xu,

Ni,

Shen

et al. 2024

AAAI

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Online advertising has been one of the most important sources for industry's growth, where the demand-side platforms (DSP) play an important role via bidding to the ad exchanges on behalf of their advertiser clients. Since more and more ad exchanges have shifted from second to first price auctions, it is challenging for DSPs to adjust bidding strategy in the volatile environment. Recent studies on bid shading in first-price auctions may have limited performance due to relatively strong hypotheses about winning probability distribution. Moreover, these studies do not consider the incentive of advertiser clients, which can be crucial for a reliable advertising platform. In this work, we consider both the optimization of bid shading technique and the design of internal auction which is ex-post incentive compatible (IC) for the management of a DSP. Firstly, we prove that the joint design of bid shading and ex-post IC auction can be reduced to choosing one monotone bid function for each advertiser without loss of optimality. Then we propose a parameterized neural network to implement the monotone bid functions. With well-designed surrogate loss, the objective can be optimized in an end-to-end manner. Finally, our experimental results demonstrate the effectiveness and superiority of our algorithm.

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Section: Additional Related Workmentioning

confidence: 99%

Section: Additional Related Workmentioning

confidence: 99%

Section: Comparison With Related Work In Bid Shadingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simultaneous Optimization of Bid Shading and Internal Auction for Demand-Side Platforms

Xu,

Ni,

Shen

et al. 2024

AAAI

View full text Add to dashboard Cite

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“…For example, Zhou et al in [19] introduced a novel deep distribution network for optimal bidding in both open and closed online first-price auctions. Zhang et al in [20] proposed a succinct and effective bid shading algorithm without parametric assumptions for the win distribution. Ren et al in [21] proposed a comprehensive framework to jointly optimize user response prediction and bid landscape forecasting.…”

Section: Related Workmentioning

confidence: 99%

Declined placental PLAC1 expression is involved in preeclampsia

et al. 2019

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Background: This study aimed to clarify the change of the expression of placenta-specific 1 (PLAC1) in the placenta of preeclamptic women and to explore the regulatory effects on thophoblast by PLAC1.Methods: Nineteen women with preeclampsia and 19 with normal pregnancies were recruited, and then we determined the expression of PLAC1 by immunohistochemistry (IHC) and Western blotting. To observe the effect of hypoxia on the expression of PLAC1, trophoblasts were cultured at the normoxia or hypoxia condition. Small interference of ribonucleic acid (siRNA) was used to silence PLAC1. The proliferation, migration and invasion of trophoblasts were evaluated with cell counting kit-8 and transwell analysis, and the apoptosis of trophoblast was evaluated by flow cytometry with FITC and PI staining.Results: Placental PLAC1 expression was significantly decreased in severe preeclampsia compared with control (P < .001). The expression of PLAC1 in trophoblasts was significantly decreased after treated with low oxygen concentration (P = .018). PLAC1 siRNA significantly inhibited the proliferation (P < .001), the migration (P < .001) and invasion (P < .001) of trophoblasts, but increased the apoptosis (P = .004 for Swan-71; P = .031 for Jar).Conclusions: The expression of PLAC1 was declined in preeclampsia and this inhibited the function of trophoblast, suggesting PLAC1 may play a role in the development of preeclampsia.

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