Weinan ZHANG 

Ph.D. Student

Department of Computer Science
University College London

5th Floor, One Euston Square
40 Melton Street, London, NW1 2FD
United Kingdom

Email: w.zhang@cs.ucl.ac.uk

I am a fourth-year Ph.D. student supervised by Dr. Jun Wang and Prof. Stephen Robertson in Media Future Group, Department of Computer Science, UCL. My research interests include machine learning, big data mining and their applications in computational advertising and recommender systems. Particularly, I focus on the research of optimal DSP bidding strategies for RTB display advertising as my Ph.D. direction. I am also interested in deep learning models and have developed several domain-specified DNNs for predicting users' online commercial behaviour. More detailed research descriptions can be found here.

Before coming to UCL, I was a research student in APEX Data and Knowledge Management Lab and a member of ACM Class in Shanghai Jiao Tong University, Shanghai, China. In addition, I was an intern at MediaGamma, Microsoft Research, Google and DERI.

Tutorials


pdf
Real-Time Bidding based Display Advertising: Mechanisms and Algorithms
Jun Wang, Shuai Yuan, Weinan Zhang
ECIR, March 2016.

link
Paper Collection of Real-Time Bidding
Weinan Zhang
Github 2015.

pdf
Research Frontier of Real-Time Bidding based Display Advertising
Weinan Zhang
Beijing, August 2015.

Publications


pdf
Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising
Weinan Zhang, Tianxiong Zhou, Jun Wang, Jian Xu
KDD 2016.   (Accept rate: 16.8%)

pdf
Deep Learning over Multi-Field Categorical Data: A Case Study on User Response Prediction
Weinan Zhang, Tianming Du, Jun Wang
ECIR 2016.   (Accept rate: 21%)

pdf
Implicit Look-alike Modelling in Display Ads: Transfer Collaborative Filtering to CTR Estimation
Weinan Zhang, Lingxi Chen, Jun Wang, Thomas Furmston
ECIR 2016.   (Accept rate: 21%)

pdf
Collective Noise Contrastive Estimation for Policy Transfer Learning
Weinan Zhang, Ulrich Paquet, Katja Hofmann
AAAI 2016.   (Accept rate: 25.8%)

pdf
Feedback Control of Real-Time Display Advertising
Weinan Zhang, Yifei Rong, Jun Wang, Tianchi Zhu, Xiaofan Wang
WSDM 2016.   (Accept rate: 18.2%)

pdf
Risk-Hedged Venture Capital Investment Recommendation
Xiaoxue Zhao*, Weinan Zhang*, Jun Wang
RecSys 2015.   (Accept rate: 21.4%)

pdf
Statistical Arbitrage Mining for Display Advertising
Weinan Zhang, Jun Wang
KDD 2015.   (Accept rate: 19.4%)

pdf
Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails
Weinan Zhang, Amr Ahmed, Jie Yang, Vanja Josifovski, Alex J. Smola
KDD 2015.   (I&G track; accept rate: 34.2%)

pdf
Optimal Real-Time Bidding for Display Advertising
Weinan Zhang, Shuai Yuan, Jun Wang
KDD 2014.   (Accept rate: 14.6%)

link
Real-Time Bidding Benchmarking with iPinYou Dataset
Weinan Zhang, Shuai Yuan, Jun Wang, Xuehua Shen
CoRR 2014.    abs/1407.7073

pdf
Bid Keyword Suggestion in Sponsored Search based on Competitiveness and Relevance
Ying Zhang, Weinan Zhang, Bin Gao, Xiaojie Yuan, Tie-Yan Liu
IPM.   2014 Vol. 50, No. 4. DOI=10.1016/j.ipm.2014.02.004

pdf
To Personalize or Not: A Risk Management Perspective
Weinan Zhang, Jun Wang, Bowei Chen, Xiaoxue Zhao
RecSys 2013.   (Accept rate: 23.8%)

pdf
An Empirical Study of Top-N Recommendation for Venture Finance
Thomas Stone, Weinan Zhang, Xiaoxue Zhao
CIKM 2013. (poster)

pdf
Interactive Collaborative Filtering
Xiaoxue Zhao*, Weinan Zhang*, Jun Wang
CIKM 2013.   (Accept rate: 16.9%)

pdf
Optimizing Top-N Collaborative Filtering via Dynamic Negative Item Sampling
Weinan Zhang, Tianqi Chen, Jun Wang, Yong Yu
SIGIR 2013. (short paper)

pdf
MeDetect: A LOD-Based System for Collective Entity Annotation in Biomedicine
Li Tian, Weinan Zhang, Antonis Bikakis, Haofen Wang, Yong Yu, Yuan Ni, Feng Cao
WI 2013.

pdf
SVDFeature: A Toolkit for Feature-based Collaborative Filtering
Tianqi Chen, Weinan Zhang, Qiuxia Lu, Kailong Chen, Zhao Zheng, Yong Yu
JMLR.    13 (2012) 3619-3622

pdf
A Semantic Approach to Recommending Text Advertisements for Images
Weinan Zhang, Li Tian, Xinruo Sun, Haofen Wang, Yong Yu
RecSys 2012.   (Accept rate: 20.2%)

pdf
Joint Optimization of Bid and Budget Allocation in Sponsored Search
Weinan Zhang, Ying Zhang, Bin Gao, Yong Yu, Xiaojie Yuan and Tie-Yan Liu
KDD 2012.  (Accept rate: 17.6%)

pdf
Serendipitous Personalized Ranking for Top-N Recommendation
Qiuxia Lu, Tianqi Chen, Weinan Zhang, Diyi Yang, Yong Yu
WI 2012.    Best paper nominee

pdf
MeDetect: Domain Entity Annotation in Biomedical References Using Linked Open Data
Li Tian, Weinan Zhang, Haofen Wang, Chenyang Wu, Yuan Ni, Feng Cao, Yong Yu
ISWC 2012. (poster)

pdf
Local Implicit Feedback Mining for Music Recommendation
Diyi Yang, Tianqi Chen, Weinan Zhang, Qiuxia Lu, Yong Yu
RecSys 2012.   (Accept rate: 20.2%)

pdf
Collaborative filtering with short term preferences mining
Diyi Yang, Tianqi Chen, Weinan Zhang, Yong Yu
SIGIR 2012. (poster)

pdf
Advertising Keywords Recommendation for Short-text Web Pages using Wikipedia
Weinan Zhang, Dingquan Wang, Gui-Rong Xue, and Hongyuan Zha
ACM TIST.    Vol. 3, No. 2. DOI=10.1145/2089094.2089112

pdf
Feature Based Informative Model for Discriminating Favorite Items from Unrated Ones
Bing Cheng, Tianqi Chen, Diyi Yang, Weinan Zhang, Yongqiang Wang, Yong Yu
APWeb 2012.

pdf
TuneSensor: A Semantic-Driven Music Recommendation Service For Digital Photo Albums
Jiansong Chao, Haofen Wang, Wenlei Zhou, Weinan Zhang and Yong Yu
ISWC 2011. (poster)

pdf
Informative Household Recommendation with Feature-based Matrix Factorization
Qiuxia Lu, Diyi Yang, Tianqi Chen, Weinan Zhang and Yong Yu
RecSys 2011.    CAMRa Workshop

pdf
Informative Ensemble of Multi-Resolution Dynamic Factorization Models
Tianqi Chen, Zhao Zheng, Qiuxia Lu, Xiao Jiang, Yuqiang Chen, Weinan Zhang, Kailong Chen, Yong Yu, Nathan N. Liu, Bin Cao, Luheng He and Qiang Yang
KDD 2011.    KDD-CUP' 11 Workshop

pdf
Feature-Based Matrix Factorization
Tianqi Chen, Zhao Zheng, Qiuxia Lu, Weinan Zhang, Yong Yu
CoRR 2011.    abs/1109.2271

pdf
LODDO: Using Linked Open Data Description Overlap to Measure Semantic Relatedness Between Named Entities
Wenlei Zhou, Haofen Wang, Jiansong Chao, Weinan Zhang and Yong Yu
JIST 2011.   

pdf
Deep Classifier for Large Scale Hierarchical Text Classification
Dingquan Wang,Weinan Zhang, Gui-Rong Xue, and Yong Yu
LSHTC 2009. (short paper)

Internships

MediaGamma Limited
Research Intern, Data Science Group, supervised by Jun Wang and Rael Cline.
London, United Kingdom    Jun. 2015 - Aug. 2015
Microsoft Research Cambridge
Research Consultant, Machine Learning and Perception Group, supervised by Ulrich Paquet and Katja Hofmann.
Cambridge, United Kingdom    Feb. 2015 - Jun. 2015
Microsoft Research Cambridge
Research Intern, Machine Learning and Perception Group, supervised by Ulrich Paquet and Thore Graepel.
Cambridge, United Kingdom    Sep. 2014 - Nov. 2014
Google Inc.
Software Engineering Intern, Strategic Technology Group, supervised by Jie Yang and Vanja Josifovski.
Mountain View, United States    Sep. 2013 - Dec. 2013
Digital Enterprise Research Institute
Research Intern, Social Software Unit, supervised by Alexandre Passant.
Galway, Ireland    Jul. 2011 - Sep. 2011
Microsoft Research Asia
Research Intern, Internet Economics & Computational Ads Group, supervised by Bin Gao and Tie-Yan Liu.
Beijing, China    Jul. 2010 - Jan. 2011

Open Source Projects

OpenBidder
An online demand-side platform for benchmarking various RTB algorithms using standard evaluation protocol and real-world ad inventory.
Report published in ArXiv.
SVDFeature
An abstract framework to build new matrix factorization variants simply by defining features.
Paper published in JMLR-MLOSS.

Datasets

iPinYou RTB Ad Logs
The first public large-scale Real-time bidding advertising log dataset, it is released after iPinYou 2013 RTB competition. We help publish the dataset on the UCL server.
Data analysis and benchmarking paper.
CrunchBase Venture Capital Investments
This dataset is collected in May 2014 based on the CrunchBase offical data API. It contains the investment records of VC firms and individual partners.
RecSys 2015 paper.

Competitions

iPinyou DSP 2013
Real-time bidding strategy optimization for demand side platforms.
CAMERa 2011
Context-aware movie recomendation challenge.
KDD Cup 2011
Yahoo! music recommendation challenge.
Yahoo! Learning to Rank Challenge 2010
Ranking top retrieved Web pages from Yahoo! search engine.
LSHTC 2009
Large-scale deep hierarchy text classification challenge.

News


13 May 2016
A full paper "Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising" is accepted in KDD 2016.

5 Dec. 2015
Two full papers about user response modelling are accepted in ECIR 2016: 1. "Deep Learning over Multi-Field Categorical Data: A Case Study on User Response Prediction"; 2. "Implicit Look-alike Modelling in Display Ads: Transfer Collaborative Filtering to CTR Estimation".

13 Nov. 2015
My internship work at Microsoft Research Cambridge "Collective Noise Contrastive Estimation for Policy Transfer Learning" is accepted as a full paper in AAAI 2016.

13 Oct. 2015
A full paper "Feedback Control of Real-Time Display Advertising" is accepted in WSDM 2016.

29 Jun. 2015
A full paper "Risk-Hedged Venture Capital Investment Recommendation" is accepted in RecSys 2015.

17 May 2015
My internship work at Google "Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails" is accepted as a full paper in KDD 2015.

13 May 2015
A full paper "Statistical Arbitrage Mining for Display Advertising" is accepted in KDD 2015.

30 Apr. 2015
I will be a program committee member in WSDM 2016.

15 Apr. 2015
We host the 3rd "London Computational Advertising & Behaviour Targeting Group" meetup with the topic "Building Big Data Models and Architecture for RTB Display Advertising". (Link)

23 Feb. 2015
I start to serve as a part-time research consultant on the project of xbox music recommendation at Microsoft Research Cambridge from now to the end of Jun. 2015.

24 Nov. 2014
We host the 2nd "London Computational Advertising & Behaviour Targeting Group" meetup with the topic "Audience Science: User Modelling and Behaviour Targeting". (Link)

25 Jun. 2014
We host the first "London Computational Advertising & Behaviour Targeting Group" meetup with the topic "Programmatic: Promise & Challenges". (Link)

19 Jun. 2014
We give a talk "Optimal Real-Time Bidding for Display Advertising" at Microsoft Research Cambridge.

13 May 2014
A full paper "Optimal Real-Time Bidding for Display Advertising" is accepted in KDD 2014.

20 Apr. 2014
I will be a research intern at Microsoft Research Cambridge from September to November 2014, doing research about large-scale Bayesian inference.

10 Apr. 2014
A journal paper "Bid Keyword Suggestion in Sponsored Search based on Competitiveness and Relevance" is accepted in IPM 2014. This is based on my first internship project at Microsoft.

20 Mar. 2014
We host the data server (located in UK) to publish the iPinYou RTB dataset. (Dataset link) To our knowledge, this is the first published RTB ads research dataset.

31 Dec. 2013
Our team "UCL-CA" wins the champion in "iPinyou Real-Time Bidding DSP Strategy Optimization" contest (season 3). (final ranking)

22 Sep. 2013
Our team "UCL-CA" wins the 3rd position in "iPinyou Real-Time Bidding DSP Strategy Optimization" contest (season 2).

23 Jul. 2013
The work "An Empirical Study of Top-N Recommendation for Venture Finance" is accepted as a 4-page short paper in CIKM 2013. This might be the first work formally bridging collaborative filtering techniques and venture finance.

20 Jul. 2013
A full paper "Interactive Collaborative Filtering" is accepted in CIKM 2013.

10 Jul. 2013
A full paper "To Personalize or Not: A Risk Management Perspective" is accepted in RecSys 2013.

16 Apr. 2013
A 4-page short paper "Optimizing Top-N Collaborative Filtering via Dynamic Negative Item Sampling" is accepted in SIGIR 2013.

28 Feb. 2013
I will be an intern at Google Mountain View from August to November, 2013, doing research about personalization in recommender systems.