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20122023
most citedWarm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

29 citations · 80 across the 15 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.MA2019★ 3 cited

Optimal Common Contract with Heterogeneous Agents

Shenke Xiao, Zihe Wang, Mengjing Chen +2

We consider the principal-agent problem with heterogeneous agents. Previous works assume that the principal signs independent incentive contracts with every agent to make them inve…

cs.LG2019

Deterministic Value-Policy Gradients

Qingpeng Cai, Ling Pan, Pingzhong Tang

Reinforcement learning algorithms such as the deep deterministic policy gradient algorithm (DDPG) has been widely used in continuous control tasks. However, the model-free DDPG alg…

cs.GT2019★ 3 cited

Optimal mechanisms with budget for user generated contents

Mengjing Chen, Pingzhong Tang, Zihe Wang +2

In this paper, we design gross product maximization mechanisms which incentivize users to upload high-quality contents on user-generated-content (UGC) websites. We show that, the p…

cs.LG2019

Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions

Feiyang Pan, Xiang Ao, Pingzhong Tang +4

It is often observed that the probabilistic predictions given by a machine learning model can disagree with averaged actual outcomes on specific subsets of data, which is also know…

cs.LG2019★ 29 cited

Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

Feiyang Pan, Shuokai Li, Xiang Ao +2

Click-through rate (CTR) prediction has been one of the most central problems in computational advertising. Lately, embedding techniques that produce low-dimensional representation…