no code implementations • 11 Mar 2024 • Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu
Therefore, identifying, quantifying, and utilizing uncertainty are essential to enhance the performance of the model for the downstream tasks as well as the reliability of the GNN predictions.
no code implementations • 14 Feb 2024 • Chen Wang, Fangxin Wang, Ruocheng Guo, Yueqing Liang, Kay Liu, Philip S. Yu
Recognizing the critical role of confidence in aligning training objectives with evaluation metrics, we propose CPFT, a versatile framework that enhances recommendation confidence by integrating Conformal Prediction (CP)-based losses with CE loss during fine-tuning.
no code implementations • 4 Feb 2024 • Duo Wu, Xianda Wang, Yaqi Qiao, Zhi Wang, Junchen Jiang, Shuguang Cui, Fangxin Wang
In this paper, we present NetLLM, the first LLM adaptation framework that efficiently adapts LLMs to solve networking problems.
no code implementations • 5 Jan 2024 • Panlong Wu, Qi Liu, Yanjie Dong, Fangxin Wang
In the first step, we optimize the seller's pricing decision and propose an Iterative Model Pricing (IMP) algorithm that optimizes the prices of large models iteratively by reasoning customers' future rental decisions, which is able to achieve a near-optimal pricing solution.
1 code implementation • 29 Dec 2023 • Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang, Philip S. Yu
One of the fundamental challenges confronting supervised graph outlier detection algorithms is the prevalent issue of class imbalance, where the scarcity of outlier instances compared to normal instances often results in suboptimal performance.
no code implementations • 26 Dec 2023 • Panlong Wu, Kangshuo Li, Ting Wang, Fangxin Wang
In this paper, we propose a novel two-stage federated learning algorithm called FedMS.
no code implementations • 19 Aug 2023 • Duo Wu, Dayou Zhang, Miao Zhang, Ruoyu Zhang, Fangxin Wang, Shuguang Cui
The high-accuracy and resource-intensive deep neural networks (DNNs) have been widely adopted by live video analytics (VA), where camera videos are streamed over the network to resource-rich edge/cloud servers for DNN inference.
no code implementations • 6 Apr 2023 • Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu
It includes a noise-resilient local solver and a robust global aggregator.
no code implementations • 27 Mar 2023 • Rongyu Zhang, Xiaowei Chi, Guiliang Liu, Wenyi Zhang, Yuan Du, Fangxin Wang
Multimodal learning has seen great success mining data features from multiple modalities with remarkable model performance improvement.
no code implementations • 7 Mar 2023 • Kaiyuan Hu, Yili Jin, Haowen Yang, Junhua Liu, Fangxin Wang
Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space.