3.7k citations · 6.9k across the 74 of their papers we have counts for
17 papers · 1 filter
Guiding the One-to-one Mapping in CycleGAN via Optimal Transport
Guansong Lu, Zhiming Zhou, Yuxuan Song +2
CycleGAN is capable of learning a one-to-one mapping between two data distributions without paired examples, achieving the task of unsupervised data translation. However, there is…
Large-scale Interactive Recommendation with Tree-structured Policy Gradient
Haokun Chen, Xinyi Dai, Han Cai +5
Reinforcement learning (RL) has recently been introduced to interactive recommender systems (IRS) because of its nature of learning from dynamic interactions and planning for long-…
AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods
Zhiming Zhou, Qingru Zhang, Guansong Lu +3
Adam is shown not being able to converge to the optimal solution in certain cases. Researchers recently propose several algorithms to avoid the issue of non-convergence of Adam, bu…
HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting
Zheyi Pan, Yuxuan Liang, Junbo Zhang +3
Spatio-temporal (ST) data, which represent multiple time series data corresponding to different spatial locations, are ubiquitous in real-world dynamic systems, such as air quality…
Sampled in Pairs and Driven by Text: A New Graph Embedding Framework
Liheng Chen, Yanru Qu, Zhenghui Wang +5
In graphs with rich texts, incorporating textual information with structural information would benefit constructing expressive graph embeddings. Among various graph embedding model…
Deep Recurrent Survival Analysis
Kan Ren, Jiarui Qin, Lei Zheng +4
Survival analysis is a hotspot in statistical research for modeling time-to-event information with data censorship handling, which has been widely used in many applications such as…
Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising
Kan Ren, Yuchen Fang, Weinan Zhang +5
In online advertising, the Internet users may be exposed to a sequence of different ad campaigns, i.e., display ads, search, or referrals from multiple channels, before led up to a…
Understanding the Effectiveness of Lipschitz-Continuity in Generative Adversarial Nets
Zhiming Zhou, Yuxuan Song, Lantao Yu +5
In this paper, we investigate the underlying factor that leads to failure and success in the training of GANs. We study the property of the optimal discriminative function and show…
Path-Level Network Transformation for Efficient Architecture Search
Han Cai, Jiacheng Yang, Weinan Zhang +2
We introduce a new function-preserving transformation for efficient neural architecture search. This network transformation allows reusing previously trained networks and existing…
Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition
Zhenghui Wang, Yanru Qu, Liheng Chen +7
We study the problem of named entity recognition (NER) from electronic medical records, which is one of the most fundamental and critical problems for medical text mining. Medical…
A Machine Learning Approach To Prevent Malicious Calls Over Telephony Networks
Huichen Li, Xiaojun Xu, Chang Liu +6
Malicious calls, i.e., telephony spams and scams, have been a long-standing challenging issue that causes billions of dollars of annual financial loss worldwide. This work presents…
QA4IE: A Question Answering based Framework for Information Extraction
Lin Qiu, Hao Zhou, Yanru Qu +7
Information Extraction (IE) refers to automatically extracting structured relation tuples from unstructured texts. Common IE solutions, including Relation Extraction (RE) and open…
Neural Text Generation: Past, Present and Beyond
Sidi Lu, Yaoming Zhu, Weinan Zhang +2
This paper presents a systematic survey on recent development of neural text generation models. Specifically, we start from recurrent neural network language models with the tradit…
Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising
Kan Ren, Weinan Zhang, Ke Chang +3
Real-time bidding (RTB) based display advertising has become one of the key technological advances in computational advertising. RTB enables advertisers to buy individual ad impres…
Collaborative Filtering with Graph-based Implicit Feedback
Minzhe Niu, Weinan Zhang, Yanru Qu +4
Introducing consumed items as users' implicit feedback in matrix factorization (MF) method, SVD++ is one of the most effective collaborative filtering methods for personalized reco…
Unsupervised Deep Domain Adaptation for Pedestrian Detection
Lihang Liu, Weiyao Lin, Lisheng Wu +2
This paper addresses the problem of unsupervised domain adaptation on the task of pedestrian detection in crowded scenes. First, we utilize an iterative algorithm to iteratively se…
Texygen: A Benchmarking Platform for Text Generation Models
Yaoming Zhu, Sidi Lu, Lei Zheng +4
We introduce Texygen, a benchmarking platform to support research on open-domain text generation models. Texygen has not only implemented a majority of text generation models, but…