Search Results for author: Wei-Nan Zhang

Found 113 papers, 58 papers with code

Counterfactual Off-Policy Training for Neural Dialogue Generation

no code implementations EMNLP 2020 Qingfu Zhu, Wei-Nan Zhang, Ting Liu, William Yang Wang

Open-domain dialogue generation suffers from the data insufficiency problem due to the vast size of potential responses.

Dialogue Generation

Technical Report on Shared Task in DialDoc21

no code implementations ACL (dialdoc) 2021 Jiapeng Li, Mingda Li, Longxuan Ma, Wei-Nan Zhang, Ting Liu

The task requires identifying the grounding knowledge in form of a document span for the next dialogue turn.

Data Augmentation

CLIP Models are Few-shot Learners: Empirical Studies on VQA and Visual Entailment

no code implementations ACL 2022 Haoyu Song, Li Dong, Wei-Nan Zhang, Ting Liu, Furu Wei

We first evaluate CLIP's zero-shot performance on a typical visual question answering task and demonstrate a zero-shot cross-modality transfer capability of CLIP on the visual entailment task.

Question Answering Visual Entailment +2

Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension Models

no code implementations26 Aug 2021 Yiming Cui, Wei-Nan Zhang, Wanxiang Che, Ting Liu, Zhigang Chen, Shijin Wang

Achieving human-level performance on some of the Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).

Machine Reading Comprehension Question Answering +1

Neural Stylistic Response Generation with Disentangled Latent Variables

no code implementations ACL 2021 Qingfu Zhu, Wei-Nan Zhang, Ting Liu, William Yang Wang

Generating open-domain conversational responses in the desired style usually suffers from the lack of parallel data in the style.

Response Generation

Profile Consistency Identification for Open-domain Dialogue Agents

1 code implementation EMNLP 2020 Haoyu Song, Yan Wang, Wei-Nan Zhang, Zhengyu Zhao, Ting Liu, Xiaojiang Liu

Maintaining a consistent attribute profile is crucial for dialogue agents to naturally converse with humans.

GIKT: A Graph-based Interaction Model for Knowledge Tracing

2 code implementations13 Sep 2020 Yang Yang, Jian Shen, Yanru Qu, Yunfei Liu, Kerong Wang, Yaoming Zhu, Wei-Nan Zhang, Yong Yu

With the rapid development in online education, knowledge tracing (KT) has become a fundamental problem which traces students' knowledge status and predicts their performance on new questions.

Knowledge Tracing

Learning to Infer User Hidden States for Online Sequential Advertising

no code implementations3 Sep 2020 Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Wei-Nan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai

To drive purchase in online advertising, it is of the advertiser's great interest to optimize the sequential advertising strategy whose performance and interpretability are both important.

reinforcement-learning

Bidirectional Model-based Policy Optimization

1 code implementation ICML 2020 Hang Lai, Jian Shen, Wei-Nan Zhang, Yong Yu

Model-based reinforcement learning approaches leverage a forward dynamics model to support planning and decision making, which, however, may fail catastrophically if the model is inaccurate.

Decision Making Model-based Reinforcement Learning

An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph

1 code implementation1 Jul 2020 Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Wei-Nan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola

To the best of our knowledge, this is the first work providing an efficient neighborhood-based interaction model in the HIN-based recommendations.

Recommendation Systems

Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

no code implementations18 Jun 2020 Sijin Zhou, Xinyi Dai, Haokun Chen, Wei-Nan Zhang, Kan Ren, Ruiming Tang, Xiuqiang He, Yong Yu

Interactive recommender system (IRS) has drawn huge attention because of its flexible recommendation strategy and the consideration of optimal long-term user experiences.

Decision Making Recommendation Systems +1

CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training

2 code implementations ACL (WebNLG, INLG) 2020 Qipeng Guo, Zhijing Jin, Xipeng Qiu, Wei-Nan Zhang, David Wipf, Zheng Zhang

Due to the difficulty and high cost of data collection, the supervised data available in the two fields are usually on the magnitude of tens of thousands, for example, 18K in the WebNLG~2017 dataset after preprocessing, which is far fewer than the millions of data for other tasks such as machine translation.

Graph Generation Knowledge Graphs +2

Multi-Agent Determinantal Q-Learning

1 code implementation ICML 2020 Yaodong Yang, Ying Wen, Li-Heng Chen, Jun Wang, Kun Shao, David Mguni, Wei-Nan Zhang

Though practical, current methods rely on restrictive assumptions to decompose the centralized value function across agents for execution.

Q-Learning

User Behavior Retrieval for Click-Through Rate Prediction

1 code implementation28 May 2020 Jiarui Qin, Wei-Nan Zhang, Xin Wu, Jiarui Jin, Yuchen Fang, Yong Yu

These retrieved behaviors are then fed into a deep model to make the final prediction instead of simply using the most recent ones.

Click-Through Rate Prediction

A Deep Recurrent Survival Model for Unbiased Ranking

1 code implementation30 Apr 2020 Jiarui Jin, Yuchen Fang, Wei-Nan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, Kun Gai

Position bias is a critical problem in information retrieval when dealing with implicit yet biased user feedback data.

Information Retrieval Survival Analysis

Counterfactual Off-Policy Training for Neural Response Generation

no code implementations29 Apr 2020 Qingfu Zhu, Wei-Nan Zhang, Ting Liu, William Yang Wang

Open-domain dialogue generation suffers from the data insufficiency problem due to the vast size of potential responses.

Dialogue Generation Response Generation

Energy-Based Imitation Learning

1 code implementation20 Apr 2020 Minghuan Liu, Tairan He, Minkai Xu, Wei-Nan Zhang

We tackle a common scenario in imitation learning (IL), where agents try to recover the optimal policy from expert demonstrations without further access to the expert or environment reward signals.

Imitation Learning reinforcement-learning

A Survey of Document Grounded Dialogue Systems (DGDS)

no code implementations17 Apr 2020 Longxuan Ma, Wei-Nan Zhang, Mingda Li, Ting Liu

We believe that extracting unstructured document(s) information is the future trend of the DS because a great amount of human knowledge lies in these document(s).

General Classification

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

4 code implementations25 Mar 2020 Bin Liu, Chenxu Zhu, Guilin Li, Wei-Nan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu

By implementing a regularized optimizer over the architecture parameters, the model can automatically identify and remove the redundant feature interactions during the training process of the model.

Click-Through Rate Prediction Recommendation Systems

Multi-Agent Interactions Modeling with Correlated Policies

1 code implementation ICLR 2020 Minghuan Liu, Ming Zhou, Wei-Nan Zhang, Yuzheng Zhuang, Jun Wang, Wulong Liu, Yong Yu

In this paper, we cast the multi-agent interactions modeling problem into a multi-agent imitation learning framework with explicit modeling of correlated policies by approximating opponents' policies, which can recover agents' policies that can regenerate similar interactions.

Imitation Learning

Discriminative Sentence Modeling for Story Ending Prediction

no code implementations19 Dec 2019 Yiming Cui, Wanxiang Che, Wei-Nan Zhang, Ting Liu, Shijin Wang, Guoping Hu

Story Ending Prediction is a task that needs to select an appropriate ending for the given story, which requires the machine to understand the story and sometimes needs commonsense knowledge.

Cloze Test

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck

no code implementations21 Nov 2019 Yuxuan Song, Lantao Yu, Zhangjie Cao, Zhiming Zhou, Jian Shen, Shuo Shao, Wei-Nan Zhang, Yong Yu

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.

Unsupervised Domain Adaptation

Contextual Recurrent Units for Cloze-style Reading Comprehension

no code implementations14 Nov 2019 Yiming Cui, Wei-Nan Zhang, Wanxiang Che, Ting Liu, Zhipeng Chen, Shijin Wang, Guoping Hu

Recurrent Neural Networks (RNN) are known as powerful models for handling sequential data, and especially widely utilized in various natural language processing tasks.

Reading Comprehension Sentiment Analysis

Exploring Diverse Expressions for Paraphrase Generation

no code implementations IJCNLP 2019 Lihua Qian, Lin Qiu, Wei-Nan Zhang, Xin Jiang, Yong Yu

Paraphrasing plays an important role in various natural language processing (NLP) tasks, such as question answering, information retrieval and sentence simplification.

Information Retrieval Paraphrase Generation +2

Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning

no code implementations10 Sep 2019 Liheng Chen, Hongyi Guo, Yali Du, Fei Fang, Haifeng Zhang, Yaoming Zhu, Ming Zhou, Wei-Nan Zhang, Qing Wang, Yong Yu

Although existing works formulate this problem into a centralized learning with decentralized execution framework, which avoids the non-stationary problem in training, their decentralized execution paradigm limits the agents' capability to coordinate.

Multi-agent Reinforcement Learning reinforcement-learning

Bi-level Actor-Critic for Multi-agent Coordination

1 code implementation8 Sep 2019 Haifeng Zhang, Weizhe Chen, Zeren Huang, Minne Li, Yaodong Yang, Wei-Nan Zhang, Jun Wang

Coordination is one of the essential problems in multi-agent systems.

Multiagent Systems

Towards Making the Most of BERT in Neural Machine Translation

1 code implementation15 Aug 2019 Jiacheng Yang, Mingxuan Wang, Hao Zhou, Chengqi Zhao, Yong Yu, Wei-Nan Zhang, Lei LI

GPT-2 and BERT demonstrate the effectiveness of using pre-trained language models (LMs) on various natural language processing tasks.

Machine Translation Translation

An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation

1 code implementation12 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.

Click-Through Rate Prediction Knowledge Graphs

Exploiting Persona Information for Diverse Generation of Conversational Responses

1 code implementation29 May 2019 Haoyu Song, Wei-Nan Zhang, Yiming Cui, Dong Wang, Ting Liu

Giving conversational context with persona information to a chatbot, how to exploit the information to generate diverse and sustainable conversations is still a non-trivial task.

Chatbot

CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms

no code implementations27 May 2019 Jiarui Jin, Ming Zhou, Wei-Nan Zhang, Minne Li, Zilong Guo, Zhiwei Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, Jieping Ye

How to optimally dispatch orders to vehicles and how to trade off between immediate and future returns are fundamental questions for a typical ride-hailing platform.

Multiagent Systems

Dynamically Fused Graph Network for Multi-hop Reasoning

1 code implementation ACL 2019 Yunxuan Xiao, Yanru Qu, Lin Qiu, Hao Zhou, Lei LI, Wei-Nan Zhang, Yong Yu

However, many difficult questions require multiple supporting evidence from scattered text among two or more documents.

Question Answering

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

1 code implementation13 May 2019 Huichu Zhang, Siyuan Feng, Chang Liu, Yaoyao Ding, Yichen Zhu, Zihan Zhou, Wei-Nan Zhang, Yong Yu, Haiming Jin, Zhenhui Li

The most commonly used open-source traffic simulator SUMO is, however, not scalable to large road network and large traffic flow, which hinders the study of reinforcement learning on traffic scenarios.

Multi-agent Reinforcement Learning reinforcement-learning

CoLight: Learning Network-level Cooperation for Traffic Signal Control

3 code implementations11 May 2019 Hua Wei, Nan Xu, Huichu Zhang, Guanjie Zheng, Xinshi Zang, Chacha Chen, Wei-Nan Zhang, Yanmin Zhu, Kai Xu, Zhenhui Li

To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication.

Multi-agent Reinforcement Learning

Deep Landscape Forecasting for Real-time Bidding Advertising

2 code implementations7 May 2019 Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Wei-Nan Zhang, Yong Yu

The problem is formulated as to forecast the probability distribution of market price for each ad auction.

Survival Analysis

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction

1 code implementation2 May 2019 Kan Ren, Jiarui Qin, Yuchen Fang, Wei-Nan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai

In order to tackle these challenges, in this paper, we propose a Hierarchical Periodic Memory Network for lifelong sequential modeling with personalized memorization of sequential patterns for each user.

Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs

1 code implementation2 Apr 2019 Zhiming Zhou, Jian Shen, Yuxuan Song, Wei-Nan Zhang, Yong Yu

Lipschitz continuity recently becomes popular in generative adversarial networks (GANs).

Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space

no code implementations4 Mar 2019 Zhou Fan, Rui Su, Wei-Nan Zhang, Yong Yu

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 networks to decompose the structured action space into simpler action spaces along with a critic network to guide the training of all sub-actor networks.

reinforcement-learning

Lipschitz Generative Adversarial Nets

1 code implementation15 Feb 2019 Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Wei-Nan Zhang, Yong Yu, Zhihua Zhang

By contrast, Wasserstein GAN (WGAN), where the discriminative function is restricted to 1-Lipschitz, does not suffer from such a gradient uninformativeness problem.

Informativeness

CommunityGAN: Community Detection with Generative Adversarial Nets

1 code implementation20 Jan 2019 Yuting Jia, Qinqin Zhang, Wei-Nan Zhang, Xinbing Wang

In this paper, we propose CommunityGAN, a novel community detection framework that jointly solves overlapping community detection and graph representation learning.

Community Detection Graph Representation Learning

Layout Design for Intelligent Warehouse by Evolution with Fitness Approximation

no code implementations14 Nov 2018 Haifeng Zhang, Zilong Guo, Han Cai, Chris Wang, Wei-Nan Zhang, Yong Yu, Wenxin Li, Jun Wang

With the rapid growth of the express industry, intelligent warehouses that employ autonomous robots for carrying parcels have been widely used to handle the vast express volume.

Large-scale Interactive Recommendation with Tree-structured Policy Gradient

no code implementations14 Nov 2018 Haokun Chen, Xinyi Dai, Han Cai, Wei-Nan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu

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-run performance.

Recommendation Systems

Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling

3 code implementations29 Oct 2018 Feng Liu, Ruiming Tang, Xutao Li, Wei-Nan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang

The DRR framework treats recommendation as a sequential decision making procedure and adopts an "Actor-Critic" reinforcement learning scheme to model the interactions between the users and recommender systems, which can consider both the dynamic adaptation and long-term rewards.

Collaborative Filtering Decision Making +3

Retrieval-Enhanced Adversarial Training for Neural Response Generation

no code implementations ACL 2019 Qingfu Zhu, Lei Cui, Wei-Nan Zhang, Furu Wei, Ting Liu

Dialogue systems are usually built on either generation-based or retrieval-based approaches, yet they do not benefit from the advantages of different models.

Response Generation

Sampled in Pairs and Driven by Text: A New Graph Embedding Framework

no code implementations12 Sep 2018 Liheng Chen, Yanru Qu, Zhenghui Wang, Lin Qiu, Wei-Nan Zhang, Ken Chen, Shaodian Zhang, Yong Yu

TGE-PS uses Pairs Sampling (PS) to improve the sampling strategy of RW, being able to reduce ~99% training samples while preserving competitive performance.

Graph Embedding Link Prediction

Factorized Q-Learning for Large-Scale Multi-Agent Systems

no code implementations11 Sep 2018 Yong Chen, Ming Zhou, Ying Wen, Yaodong Yang, Yufeng Su, Wei-Nan Zhang, Dell Zhang, Jun Wang, Han Liu

Deep Q-learning has achieved a significant success in single-agent decision making tasks.

Multiagent Systems

Learning Adaptive Display Exposure for Real-Time Advertising

no code implementations10 Sep 2018 Weixun Wang, Junqi Jin, Jianye Hao, Chunjie Chen, Chuan Yu, Wei-Nan Zhang, Jun Wang, Xiaotian Hao, Yixi Wang, Han Li, Jian Xu, Kun Gai

In this paper, we investigate the problem of advertising with adaptive exposure: can we dynamically determine the number and positions of ads for each user visit under certain business constraints so that the platform revenue can be increased?

Deep Recurrent Survival Analysis

1 code implementation7 Sep 2018 Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Wei-Nan Zhang, Lin Qiu, Yong Yu

By capturing the time dependency through modeling the conditional probability of the event for each sample, our method predicts the likelihood of the true event occurrence and estimates the survival rate over time, i. e., the probability of the non-occurrence of the event, for the censored data.

Survival Analysis

Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising

1 code implementation11 Aug 2018 Kan Ren, Yuchen Fang, Wei-Nan Zhang, Shuhao Liu, Jiajun Li, Ya zhang, Yong Yu, Jun Wang

To achieve this, we utilize sequence-to-sequence prediction for user clicks, and combine both post-view and post-click attribution patterns together for the final conversion estimation.

Zero Pronoun Resolution with Attention-based Neural Network

1 code implementation COLING 2018 Qingyu Yin, Yu Zhang, Wei-Nan Zhang, Ting Liu, William Yang Wang

Recent neural network methods for zero pronoun resolution explore multiple models for generating representation vectors for zero pronouns and their candidate antecedents.

Chinese Zero Pronoun Resolution

Context-Sensitive Generation of Open-Domain Conversational Responses

no code implementations COLING 2018 Wei-Nan Zhang, Yiming Cui, Yifa Wang, Qingfu Zhu, Lingzhi Li, Lianqiang Zhou, Ting Liu

Despite the success of existing works on single-turn conversation generation, taking the coherence in consideration, human conversing is actually a context-sensitive process.

Information Retrieval Machine Translation

AceKG: A Large-scale Knowledge Graph for Academic Data Mining

no code implementations23 Jul 2018 Ruijie Wang, Yuchen Yan, Jialu Wang, Yuting Jia, Ye Zhang, Wei-Nan Zhang, Xinbing Wang

Most existing knowledge graphs (KGs) in academic domains suffer from problems of insufficient multi-relational information, name ambiguity and improper data format for large-scale machine processing.

Community Detection Entity Alignment +3

Understanding the Effectiveness of Lipschitz-Continuity in Generative Adversarial Nets

1 code implementation2 Jul 2018 Zhiming Zhou, Yuxuan Song, Lantao Yu, Hongwei Wang, Jiadong Liang, Wei-Nan Zhang, Zhihua Zhang, Yong Yu

In this paper, we investigate the underlying factor that leads to failure and success in the training of GANs.

Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data

7 code implementations1 Jul 2018 Yanru Qu, Bohui Fang, Wei-Nan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, Xiuqiang He

User response prediction is a crucial component for personalized information retrieval and filtering scenarios, such as recommender system and web search.

Click-Through Rate Prediction Feature Engineering +2

Generative Adversarial Nets for Information Retrieval: Fundamentals and Advances

no code implementations10 Jun 2018 Wei-Nan Zhang

In this tutorial, we focus on discussing the GAN techniques and the variants on discrete data fitting in various information retrieval scenarios.

Information Retrieval Text Generation

Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition

no code implementations NAACL 2018 Zhenghui Wang, Yanru Qu, Li-Heng Chen, Jian Shen, Wei-Nan Zhang, Shaodian Zhang, Yimei Gao, Gen Gu, Ken Chen, Yong Yu

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 Named Entity Recognition NER +1

Optimizing Sponsored Search Ranking Strategy by Deep Reinforcement Learning

no code implementations20 Mar 2018 Li He, Liang Wang, Kaipeng Liu, Bo Wu, Wei-Nan Zhang

From the advertisers' side, participating in ranking the search results by paying for the sponsored search advertisement to attract more awareness and purchase facilitates their commercial goal.

online learning reinforcement-learning

Neural Text Generation: Past, Present and Beyond

no code implementations15 Mar 2018 Sidi Lu, Yaoming Zhu, Wei-Nan Zhang, Jun Wang, Yong Yu

This paper presents a systematic survey on recent development of neural text generation models.

reinforcement-learning Text Generation

Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising

no code implementations1 Mar 2018 Kan Ren, Wei-Nan Zhang, Ke Chang, Yifei Rong, Yong Yu, Jun Wang

From the learning perspective, we show that the bidding machine can be updated smoothly with both offline periodical batch or online sequential training schemes.

Texygen: A Benchmarking Platform for Text Generation Models

1 code implementation6 Feb 2018 Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Wei-Nan Zhang, Jun Wang, Yong Yu

We introduce Texygen, a benchmarking platform to support research on open-domain text generation models.

Text Generation

MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence

3 code implementations2 Dec 2017 Lianmin Zheng, Jiacheng Yang, Han Cai, Wei-Nan Zhang, Jun Wang, Yong Yu

Unlike previous research platforms on single or multi-agent reinforcement learning, MAgent focuses on supporting the tasks and the applications that require hundreds to millions of agents.

Multi-agent Reinforcement Learning reinforcement-learning

A Neural Stochastic Volatility Model

no code implementations30 Nov 2017 Rui Luo, Wei-Nan Zhang, Xiaojun Xu, Jun Wang

In this paper, we show that the recent integration of statistical models with deep recurrent neural networks provides a new way of formulating volatility (the degree of variation of time series) models that have been widely used in time series analysis and prediction in finance.

Time Series Time Series Analysis

Improving Negative Sampling for Word Representation using Self-embedded Features

no code implementations26 Oct 2017 Long Chen, Fajie Yuan, Joemon M. Jose, Wei-Nan Zhang

Although the word-popularity based negative sampler has shown superb performance in the skip-gram model, the theoretical motivation behind oversampling popular (non-observed) words as negative samples is still not well understood.

Face Transfer with Generative Adversarial Network

no code implementations17 Oct 2017 Runze Xu, Zhiming Zhou, Wei-Nan Zhang, Yong Yu

Face transfer animates the facial performances of the character in the target video by a source actor.

Face Transfer

The First Evaluation of Chinese Human-Computer Dialogue Technology

2 code implementations29 Sep 2017 Wei-Nan Zhang, Zhigang Chen, Wanxiang Che, Guoping Hu, Ting Liu

In this paper, we introduce the first evaluation of Chinese human-computer dialogue technology.

Intent Classification

Long Text Generation via Adversarial Training with Leaked Information

6 code implementations24 Sep 2017 Jiaxian Guo, Sidi Lu, Han Cai, Wei-Nan Zhang, Yong Yu, Jun Wang

Automatically generating coherent and semantically meaningful text has many applications in machine translation, dialogue systems, image captioning, etc.

Text Generation

A Study of AI Population Dynamics with Million-agent Reinforcement Learning

no code implementations13 Sep 2017 Yaodong Yang, Lantao Yu, Yiwei Bai, Jun Wang, Wei-Nan Zhang, Ying Wen, Yong Yu

We conduct an empirical study on discovering the ordered collective dynamics obtained by a population of intelligence agents, driven by million-agent reinforcement learning.

reinforcement-learning

Chinese Zero Pronoun Resolution with Deep Memory Network

no code implementations EMNLP 2017 Qingyu Yin, Yu Zhang, Wei-Nan Zhang, Ting Liu

Existing approaches for Chinese zero pronoun resolution typically utilize only syntactical and lexical features while ignoring semantic information.

Chinese Zero Pronoun Resolution Feature Engineering +1

Inception Score, Label Smoothing, Gradient Vanishing and -log(D(x)) Alternative

no code implementations5 Aug 2017 Zhiming Zhou, Wei-Nan Zhang, Jun Wang

In this article, we mathematically study several GAN related topics, including Inception score, label smoothing, gradient vanishing and the -log(D(x)) alternative.

Efficient Architecture Search by Network Transformation

3 code implementations16 Jul 2017 Han Cai, Tianyao Chen, Wei-Nan Zhang, Yong Yu, Jun Wang

Techniques for automatically designing deep neural network architectures such as reinforcement learning based approaches have recently shown promising results.

Image Classification Neural Architecture Search +1

Learning to Design Games: Strategic Environments in Reinforcement Learning

no code implementations5 Jul 2017 Haifeng Zhang, Jun Wang, Zhiming Zhou, Wei-Nan Zhang, Ying Wen, Yong Yu, Wenxin Li

In typical reinforcement learning (RL), the environment is assumed given and the goal of the learning is to identify an optimal policy for the agent taking actions through its interactions with the environment.

reinforcement-learning

Wasserstein Distance Guided Representation Learning for Domain Adaptation

8 code implementations5 Jul 2017 Jian Shen, Yanru Qu, Wei-Nan Zhang, Yong Yu

Inspired by Wasserstein GAN, in this paper we propose a novel approach to learn domain invariant feature representations, namely Wasserstein Distance Guided Representation Learning (WDGRL).

Domain Adaptation General Classification +2

IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models

1 code implementation30 May 2017 Jun Wang, Lantao Yu, Wei-Nan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, Dell Zhang

This paper provides a unified account of two schools of thinking in information retrieval modelling: the generative retrieval focusing on predicting relevant documents given a query, and the discriminative retrieval focusing on predicting relevancy given a query-document pair.

Document Ranking Information Retrieval +1

Real-Time Bidding by Reinforcement Learning in Display Advertising

1 code implementation10 Jan 2017 Han Cai, Kan Ren, Wei-Nan Zhang, Kleanthis Malialis, Jun Wang, Yong Yu, Defeng Guo

In this paper, we formulate the bid decision process as a reinforcement learning problem, where the state space is represented by the auction information and the campaign's real-time parameters, while an action is the bid price to set.

reinforcement-learning

Neural Personalized Response Generation as Domain Adaptation

no code implementations9 Jan 2017 Wei-Nan Zhang, Ting Liu, Yifa Wang, Qingfu Zhu

Moreover, the lexical divergence of the responses generated by the 5 personalized models indicates that the proposed two-phase approach achieves good results on modeling the responding style of human and generating personalized responses for the conversational systems.

Domain Adaptation Response Generation

Product-based Neural Networks for User Response Prediction

10 code implementations1 Nov 2016 Yanru Qu, Han Cai, Kan Ren, Wei-Nan Zhang, Yong Yu, Ying Wen, Jun Wang

Predicting user responses, such as clicks and conversions, is of great importance and has found its usage in many Web applications including recommender systems, web search and online advertising.

Click-Through Rate Prediction Recommendation Systems

Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting

1 code implementation7 Oct 2016 Jun Wang, Wei-Nan Zhang, Shuai Yuan

The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads.

Computer Science and Game Theory

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

22 code implementations18 Sep 2016 Lantao Yu, Wei-Nan Zhang, Jun Wang, Yong Yu

As a new way of training generative models, Generative Adversarial Nets (GAN) that uses a discriminative model to guide the training of the generative model has enjoyed considerable success in generating real-valued data.

Text Generation

Learning to Start for Sequence to Sequence Architecture

no code implementations19 Aug 2016 Qingfu Zhu, Wei-Nan Zhang, Lianqiang Zhou, Ting Liu

An obvious drawback of these work is that there is not a learnable relationship between words and the start symbol.

Machine Translation Response Generation +2

Learning text representation using recurrent convolutional neural network with highway layers

no code implementations22 Jun 2016 Ying Wen, Wei-Nan Zhang, Rui Luo, Jun Wang

Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks.

Sentiment Analysis

Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution

no code implementations ACL 2017 Ting Liu, Yiming Cui, Qingyu Yin, Wei-Nan Zhang, Shijin Wang, Guoping Hu

Most existing approaches for zero pronoun resolution are heavily relying on annotated data, which is often released by shared task organizers.

Reading Comprehension

Neural Recovery Machine for Chinese Dropped Pronoun

no code implementations7 May 2016 Wei-Nan Zhang, Ting Liu, Qingyu Yin, Yu Zhang

Dropped pronouns (DPs) are ubiquitous in pro-drop languages like Chinese, Japanese etc.

Feature Engineering

A Deep Neural Network for Chinese Zero Pronoun Resolution

no code implementations20 Apr 2016 Qingyu Yin, Wei-Nan Zhang, Yu Zhang, Ting Liu

This is because zero pronouns have no descriptive information, which results in difficulty in explicitly capturing their semantic similarities with antecedents.

Chinese Zero Pronoun Resolution

Feedback Control of Real-Time Display Advertising

1 code implementation3 Mar 2016 Wei-Nan Zhang, Yifei Rong, Jun Wang, Tianchi Zhu, Xiaofan Wang

In this paper, we propose a feedback control mechanism for RTB which helps advertisers dynamically adjust the bids to effectively control the KPIs, e. g., the auction winning ratio and the effective cost per click.

Computer Science and Game Theory Systems and Control

Implicit Look-alike Modelling in Display Ads: Transfer Collaborative Filtering to CTR Estimation

no code implementations11 Jan 2016 Wei-Nan Zhang, Lingxi Chen, Jun Wang

In this work, we propose a general framework which learns the user profiles based on their online browsing behaviour, and transfers the learned knowledge onto prediction of their ad response.

Collaborative Filtering Transfer Learning

Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction

4 code implementations11 Jan 2016 Wei-Nan Zhang, Tianming Du, Jun Wang

Different from continuous raw features that we usually found in the image and audio domains, the input features in web space are always of multi-field and are mostly discrete and categorical while their dependencies are little known.

Click-Through Rate Prediction

Real-Time Bidding Benchmarking with iPinYou Dataset

2 code implementations25 Jul 2014 Wei-Nan Zhang, Shuai Yuan, Jun Wang, Xuehua Shen

This dataset directly supports the experiments of some important research problems such as bid optimisation and CTR estimation.

Computer Science and Game Theory Computers and Society

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