1 code implementation • 8 May 2024 • Nian Liu, Shen Fan, Ting Bai, Peng Wang, Mingwei Sun, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Chuan Shi
In this paper, we propose a novel social recommendation method called LSIR (\textbf{L}earning \textbf{S}ocial Graph for \textbf{I}nactive User \textbf{R}ecommendation) that learns an optimal social graph structure for social recommendation, especially for inactive users.
no code implementations • 21 Jan 2024 • Xinfeng Ru, Weiguo Xia, Ting Bai
A distributed model predictive control (MPC) method is then presented to assign the green times.
1 code implementation • 12 Nov 2023 • Ting Bai, Yuchao Li, Karl Henrik Johansson, Jonas Mårtensson
Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial.
no code implementations • 18 Oct 2023 • Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains.
no code implementations • 21 Jul 2023 • Ting Bai, Alexander Johansson, Karl Henrik Johansson, Jonas Mårtensson
This paper presents a distributed framework for addressing multi-fleet platoon coordination in large transportation networks, where each truck has a fixed route and aims to maximize its own fleet's platooning profit by scheduling its waiting times at hubs.
no code implementations • 19 Jul 2023 • Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs.
1 code implementation • 21 Apr 2023 • Zhen Tian, Ting Bai, Wayne Xin Zhao, Ji-Rong Wen, Zhao Cao
EulerNet converts the exponential powers of feature interactions into simple linear combinations of the modulus and phase of the complex features, making it possible to adaptively learn the high-order feature interactions in an efficient way.
no code implementations • 15 Mar 2023 • Ting Bai, Yuchao Li, Karl H. Johansson, Jonas Mårtensson
We assume that a collection of charging and rest stations is given along a pre-planned route with known detours and that the problem data are deterministic.
1 code implementation • 21 Nov 2022 • Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao
Some recent knowledge distillation based methods transfer knowledge from complex teacher models to shallow student models for accelerating the online model inference.
no code implementations • 19 Aug 2022 • Ting Bai, Alexander Johansson, Karl Henrik Johansson, Jonas Mårtensson
In our problem, trucks have fixed routes in a transportation network and can wait at hubs along their routes to form platoons with others while fulfilling the driving and rest time constraints.
no code implementations • 21 Feb 2022 • Ting Bai, Alexander Johansson, ShaoYuan Li, Jonas Mårtensson
To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network.
no code implementations • 18 Feb 2022 • Ting Bai, Alexander Johansson, Karl Henrik Johansson, Jonas Mårtensson
This paper considers the problem of hub-based platoon coordination for a large-scale transport system, where trucks have individual utility functions to optimize.
1 code implementation • 13 May 2021 • Fangtao Li, Ting Bai, Chenyu Cao, Zihe Liu, Chenghao Yan, Bin Wu
Video Question Answering (VideoQA) is a challenging video understanding task since it requires a deep understanding of both question and video.
1 code implementation • 12 Aug 2019 • Yanru Qu, Ting Bai, Wei-Nan Zhang, Jian-Yun Nie, Jian Tang
This paper studies graph-based recommendation, where an interaction graph is constructed from historical records and is lever-aged to alleviate data sparsity and cold start problems.
Ranked #2 on Click-Through Rate Prediction on MovieLens 1M
no code implementations • NAACL 2019 • Peng Lu, Ting Bai, Philippe Langlais
Multi-task learning (MTL) has been studied recently for sequence labeling.
no code implementations • 12 Feb 2019 • Ting Bai, Pan Du, Wayne Xin Zhao, Ji-Rong Wen, Jian-Yun Nie
Recommending the right products is the central problem in recommender systems, but the right products should also be recommended at the right time to meet the demands of users, so as to maximize their values.