3.7k citations · 6.9k across the 74 of their papers we have counts for
13 papers · 1 filter
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Yuxuan Song, Lantao Yu, Zhangjie Cao +5
Domain adaptation aims to leverage the supervision signal of source domain to obtain an accurate model for target domain, where the labels are not available. To leverage and adapt…
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling
Jiarui Qin, Kan Ren, Yuchen Fang +2
Sequential recommendation task aims to predict user preference over items in the future given user historical behaviors. The order of user behaviors implies that there are resource…
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching
Ming Zhou, Jiarui Jin, Weinan Zhang +6
Improving the efficiency of dispatching orders to vehicles is a research hotspot in online ride-hailing systems. Most of the existing solutions for order-dispatching are centralize…
Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning
Liheng Chen, Hongyi Guo, Yali Du +7
In many real-world problems, a team of agents need to collaborate to maximize the common reward. Although existing works formulate this problem into a centralized learning with dec…
Towards Making the Most of BERT in Neural Machine Translation
Jiacheng Yang, Mingxuan Wang, Hao Zhou +4
GPT-2 and BERT demonstrate the effectiveness of using pre-trained language models (LMs) on various natural language processing tasks. However, LM fine-tuning often suffers from cat…
Dynamically Fused Graph Network for Multi-hop Reasoning
Yunxuan Xiao, Yanru Qu, Lin Qiu +4
Text-based question answering (TBQA) has been studied extensively in recent years. Most existing approaches focus on finding the answer to a question within a single paragraph. How…
Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence
Yaoming Zhu, Juncheng Wan, Zhiming Zhou +5
Knowledge base is one of the main forms to represent information in a structured way. A knowledge base typically consists of Resource Description Frameworks (RDF) triples which des…
CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
Huichu Zhang, Siyuan Feng, Chang Liu +7
Traffic signal control is an emerging application scenario for reinforcement learning. Besides being as an important problem that affects people's daily life in commuting, traffic…
Deep Landscape Forecasting for Real-time Bidding Advertising
Kan Ren, Jiarui Qin, Lei Zheng +3
The emergence of real-time auction in online advertising has drawn huge attention of modeling the market competition, i.e., bid landscape forecasting. The problem is formulated as…
Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
Kan Ren, Jiarui Qin, Yuchen Fang +8
User response prediction, which models the user preference w.r.t. the presented items, plays a key role in online services. With two-decade rapid development, nowadays the cumulate…
Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs
Zhiming Zhou, Jian Shen, Yuxuan Song +2
Lipschitz continuity recently becomes popular in generative adversarial networks (GANs). It was observed that the Lipschitz regularized discriminator leads to improved training sta…
Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space
Zhou Fan, Rui Su, Weinan Zhang +1
In this paper we propose a hybrid architecture of actor-critic algorithms for reinforcement learning in parameterized action space, which consists of multiple parallel sub-actor ne…
Lipschitz Generative Adversarial Nets
Zhiming Zhou, Jiadong Liang, Yuxuan Song +5
In this paper, we study the convergence of generative adversarial networks (GANs) from the perspective of the informativeness of the gradient of the optimal discriminative function…