1 code implementation • 5 Mar 2024 • Wenjie Wang, Changsheng Wang, Fuli Feng, Wentao Shi, Daizong Ding, Tat-Seng Chua
UBA estimates the treatment effect on each target user and optimizes the allocation of fake user budgets to maximize the attack performance.
1 code implementation • 29 Feb 2024 • Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng
To this end, we propose a Bi-level Learnable LLM Planner framework, which consists of a set of LLM instances and breaks down the learning process into macro-learning and micro-learning to learn macro-level guidance and micro-level personalized recommendation policies, respectively.
no code implementations • 29 Feb 2024 • Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He
Compared to AUC, LLPAUC considers only the partial area under the ROC curve in the Lower-Left corner to push the optimization focus on Top-K. We provide theoretical validation of the correlation between LLPAUC and Top-K ranking metrics and demonstrate its robustness to noisy user feedback.
1 code implementation • 28 Feb 2024 • Jizhi Zhang, Keqin Bao, Wenjie Wang, Yang Zhang, Wentao Shi, Wanhong Xu, Fuli Feng, Tat-Seng Chua
Additionally, we prospect the evolution of Rec4Agentverse and conceptualize it into three stages based on the enhancement of the interaction and information exchange among Agent Items, Agent Recommender, and the user.
1 code implementation • 20 Dec 2023 • Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang
Loss functions steer the optimization direction of recommendation models and are critical to model performance, but have received relatively little attention in recent recommendation research.
no code implementations • 7 Feb 2023 • Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He
Specifically, they suffer from two main limitations: 1) existing Graph Convolutional Network (GCN) methods in hyperbolic space rely on tangent space approximation, which would incur approximation error in representation learning, and 2) due to the lack of inner product operation definition in hyperbolic space, existing methods can only measure the plausibility of facts (links) with hyperbolic distance, which is difficult to capture complex data patterns.
1 code implementation • 7 Feb 2023 • Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He
Secondly, we prove that OPAUC has a stronger connection with Top-K evaluation metrics than AUC and verify it with simulation experiments.
1 code implementation • 25 Nov 2022 • Jing Xu, Wentao Shi, Pan Gao, Zhengwei Wang, Qizhu Li
On the more challenging ADE20K dataset, our best model yields a single-scale mIoU of 50. 18, and a multi-scale mIoU of 51. 8, which is on-par with the current state-of-art model, while we drastically cut the number of FLOPs by 53. 5%.
1 code implementation • 3 Aug 2022 • Wentao Shi, Jing Xu, Pan Gao
It is well believed that Transformer performs better in semantic segmentation compared to convolutional neural networks.
no code implementations • 14 Jul 2022 • Wei Gao, Jie Chen, Cédric Richard, Wentao Shi, Qunfei Zhang
We propose the adaptive random Fourier features Gaussian kernel LMS (ARFF-GKLMS).
no code implementations • 14 Sep 2021 • Wei Gao, Jie Chen, Cédric Richard, Wentao Shi, Qunfei Zhang
The recursive least-squares algorithm with $\ell_1$-norm regularization ($\ell_1$-RLS) exhibits excellent performance in terms of convergence rate and steady-state error in identification of sparse systems.
2 code implementations • 22 Aug 2021 • Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He
Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks.
2 code implementations • Bioinformatics 2020 • Wentao Shi, Jeffrey M Lemoine, Abd-El-Monsif A Shawky, Manali Singha, Limeng Pu, Shuangyan Yang, J Ramanujam, Michal Brylinski
Availability and implementation BionoiNet is implemented in Python with the source code freely available at: https://github. com/CSBG-LSU/BionoiNet.