activity
20192022
most citedAn Efficient Deep Distribution Network for Bid Shading in First-Price Auctions

29 citations · 52 across the 5 of their papers we have counts for

collaborators

6 papers

stat.ML2021

Mid-flight Forecasting for CPA Lines in Online Advertising

Hao He, Tian Zhou, Lihua Ren +2

For Verizon MediaDemand Side Platform(DSP), forecasting of ad campaign performance not only feeds key information to the optimization server to allow the system to operate on a hig…

cs.GT202129 cited

An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions

Tian Zhou, Hao He, Shengjun Pan +9

Since 2019, most ad exchanges and sell-side platforms (SSPs), in the online advertising industry, shifted from second to first price auctions. Due to the fundamental difference bet…

cs.CV20218 cited

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

Xiangtai Li, Hao He, Xia Li +6

Aerial Image Segmentation is a particular semantic segmentation problem and has several challenging characteristics that general semantic segmentation does not have. There are two…

cs.GT202012 cited

Bid Shading by Win-Rate Estimation and Surplus Maximization

Shengjun Pan, Brendan Kitts, Tian Zhou +8

This paper describes a new win-rate based bid shading algorithm (WR) that does not rely on the minimum-bid-to-win feedback from a Sell-Side Platform (SSP). The method uses a modifi…

cs.LG2019

Truly Proximal Policy Optimization

Yuhui Wang, Hao He, Chao Wen +1

Proximal policy optimization (PPO) is one of the most successful deep reinforcement-learning methods, achieving state-of-the-art performance across a wide range of challenging task…

cs.LG2019

Trust Region-Guided Proximal Policy Optimization

Yuhui Wang, Hao He, Xiaoyang Tan +1

Proximal policy optimization (PPO) is one of the most popular deep reinforcement learning (RL) methods, achieving state-of-the-art performance across a wide range of challenging ta…