Search Results for author: Yongkang Wang

Found 14 papers, 4 papers with code

Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation

1 code implementation31 May 2024 Zhiwei Wang, Yongkang Wang, Wen Zhang

Additionally, the ablation studies and visualizations demonstrate the superiority of MIPE owing to the better representations acquired through multi-modal contrastive learning and the interaction patterns comprehended by the interaction informativeness estimation.

Contrastive Learning Informativeness

Deep Automated Mechanism Design for Integrating Ad Auction and Allocation in Feed

no code implementations3 Jan 2024 Xuejian Li, Ze Wang, Bingqi Zhu, Fei He, Yongkang Wang, Xingxing Wang

The prevalent methods of segregating the ad auction and allocation into two distinct stages face two problems: 1) Ad auction does not consider externalities, such as the influence of actual display position and context on ad Click-Through Rate (CTR); 2) The ad allocation, which utilizes the auction-winning ad's payment to determine the display position dynamically, fails to maintain incentive compatibility (IC) for the advertisement.

Position

A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation

1 code implementation25 Dec 2023 Yongkang Wang, Xuan Liu, Feng Huang, Zhankun Xiong, Wen Zhang

Therapeutic peptides represent a unique class of pharmaceutical agents crucial for the treatment of human diseases.

Contrastive Learning Diversity

MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed

no code implementations17 Apr 2023 Xiaowen Shi, Ze Wang, Yuanying Cai, Xiaoxu Wu, Fan Yang, Guogang Liao, Yongkang Wang, Xingxing Wang, Dong Wang

There are two types of data employed to train reinforcement learning (RL) model for position allocation, named strategy data and random data.

Imitation Learning Position +2

PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce

1 code implementation6 Feb 2023 Xiaowen Shi, Fan Yang, Ze Wang, Xiaoxu Wu, Muzhi Guan, Guogang Liao, Yongkang Wang, Xingxing Wang, Dong Wang

Then we design a novel omnidirectional attention mechanism in OCPM to capture the context information in the permutation.

Re-Ranking

A Deep Behavior Path Matching Network for Click-Through Rate Prediction

no code implementations1 Feb 2023 Jian Dong, Yisong Yu, Yapeng Zhang, Yimin Lv, Shuli Wang, Beihong Jin, Yongkang Wang, Xingxing Wang, Dong Wang

User behaviors on an e-commerce app not only contain different kinds of feedback on items but also sometimes imply the cognitive clue of the user's decision-making.

Click-Through Rate Prediction Contrastive Learning +1

NMA: Neural Multi-slot Auctions with Externalities for Online Advertising

no code implementations20 May 2022 Guogang Liao, Xuejian Li, Ze Wang, Fan Yang, Muzhi Guan, Bingqi Zhu, Yongkang Wang, Xingxing Wang, Dong Wang

Although VCG-based multi-slot auctions (e. g., VCG, WVCG) make it theoretically possible to model global externalities (e. g., the order and positions of ads and so on), they lack an efficient balance of both revenue and social welfare.

Learning List-wise Representation in Reinforcement Learning for Ads Allocation with Multiple Auxiliary Tasks

no code implementations2 Apr 2022 Ze Wang, Guogang Liao, Xiaowen Shi, Xiaoxu Wu, Chuheng Zhang, Yongkang Wang, Xingxing Wang, Dong Wang

With the recent prevalence of reinforcement learning (RL), there have been tremendous interests in utilizing RL for ads allocation in recommendation platforms (e. g., e-commerce and news feed sites).

Contrastive Learning Reinforcement Learning (RL)

Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation

no code implementations2 Apr 2022 Ze Wang, Guogang Liao, Xiaowen Shi, Xiaoxu Wu, Chuheng Zhang, Bingqi Zhu, Yongkang Wang, Xingxing Wang, Dong Wang

Ads allocation, which involves allocating ads and organic items to limited slots in feed with the purpose of maximizing platform revenue, has become a research hotspot.

reinforcement-learning Reinforcement Learning (RL)

Deep Page-Level Interest Network in Reinforcement Learning for Ads Allocation

no code implementations1 Apr 2022 Guogang Liao, Xiaowen Shi, Ze Wang, Xiaoxu Wu, Chuheng Zhang, Yongkang Wang, Xingxing Wang, Dong Wang

A mixed list of ads and organic items is usually displayed in feed and how to allocate the limited slots to maximize the overall revenue is a key problem.

Click-Through Rate Prediction reinforcement-learning +1

Cross DQN: Cross Deep Q Network for Ads Allocation in Feed

1 code implementation9 Sep 2021 Guogang Liao, Ze Wang, Xiaoxu Wu, Xiaowen Shi, Chuheng Zhang, Yongkang Wang, Xingxing Wang, Dong Wang

Our model results in higher revenue and better user experience than state-of-the-art baselines in offline experiments.

Cannot find the paper you are looking for? You can Submit a new open access paper.