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• name: description content: Weinan Zhang, Full Professor in Shanghai Jiao Tong University. Research topics include reinforcement learning, data science, robotics, recommender systems. Former intern at Microsoft, Google and DERI.
• name: keywords content: weinan zhang, sjtu, shanghai jiao tong university, ucl, university college london, reinforcement learning, data science, robotics, recommender systems, information retrieval
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• http://wnzhang.net/teaching/cs420/index.html
• https://wnzhang.net/teaching/sjtu-rl-2024/
• http://wnzhang.net/teaching/ee448/index.html
• http://wnzhang.net/./teaching/sjtu-rl-2024/slides/rl-turorial-3h-rlchina2024.pdf
• http://wnzhang.net/./tutorials/marl2018/index.html
• http://wnzhang.net/./tutorials/sigir2018/index.html
• http://wnzhang.net/./slides/ecir16-rtb.pdf
• http://wnzhang.net/./papers/to-appear.html
• http://wnzhang.net/./papers/2023-tois-ubr.pdf
• http://wnzhang.net/./papers/2023-kdd-coaltag.pdf
• http://wnzhang.net/./papers/2023-kdd-dir.pdf
• http://wnzhang.net/./papers/2023-kdd-dert.pdf
• http://wnzhang.net/./papers/2022-iconip-hgrkt.pdf
• http://wnzhang.net/./papers/2022-iconip-mltc.pdf
• http://wnzhang.net/./papers/2022-tkde-stmetanet+.pdf
• http://wnzhang.net/./papers/2022-pr-cutranking.pdf
• http://wnzhang.net/./papers/2022-wsdm-cokt.pdf
• http://wnzhang.net/./papers/2021-dai-sic.pdf
• http://wnzhang.net/./papers/2021-cikm-literatureqa.pdf
• http://wnzhang.net/./papers/2021-tois-urank+.pdf
• http://wnzhang.net/./papers/2021-sigir-iekt.pdf
• http://wnzhang.net/./papers/2021-sigir-graphcm.pdf
• http://wnzhang.net/./papers/1m-agents-aamas.pdf
• http://wnzhang.net/./papers/nsvm-aaai.pdf
• http://wnzhang.net/./papers/nce-tl-cikm.pdf
• http://wnzhang.net/./papers/rl-rank-cikm.pdf
• http://wnzhang.net/./papers/dadm-kdd.pdf
• http://wnzhang.net/./papers/boostfm.pdf
• http://wnzhang.net/./papers/rlb.pdf
• http://wnzhang.net/./papers/risk-bid.pdf
• http://wnzhang.net/./papers/lambdafm.pdf
• http://wnzhang.net/./papers/unbias-kdd.pdf
• http://wnzhang.net/./share/rtb-papers/deep-ctr.pdf
• http://wnzhang.net/./share/rtb-papers/cf-ctr.pdf
• http://wnzhang.net/./papers/collect-nce-aaai.pdf
• http://wnzhang.net/./papers/fc-wsdm.pdf
• RecSys 2015 paper
• http://wnzhang.net/./papers/sam-kdd.pdf
• http://wnzhang.net/./papers/em-crf-kdd.pdf
• http://wnzhang.net/./papers/ortb-kdd.pdf
• http://wnzhang.net/./papers/nkr-ipm.pdf
• http://wnzhang.net/./papers/two-portfolio-recsys.pdf
• http://wnzhang.net/./papers/venture-cikm.pdf
• http://wnzhang.net/./papers/icf-cikm.pdf
• http://wnzhang.net/./papers/lambdarankcf-sigir.pdf
• http://wnzhang.net/./papers/medetect-wi.pdf
• http://wnzhang.net/./papers/svdfeature-jmlr.pdf
• http://wnzhang.net/./papers/iadsense-recsys.pdf
• http://wnzhang.net/./papers/jointopt-kdd.pdf
• http://wnzhang.net/./papers/seren-wi.pdf
• http://wnzhang.net/./papers/medetect-iswc.pdf
• http://wnzhang.net/./papers/multi-imfb-recsys.pdf
• http://wnzhang.net/./papers/multi-imfb-sigir.pdf
• http://wnzhang.net/./papers/keywords-tist.pdf
• http://wnzhang.net/./papers/cb-apweb.pdf
• http://wnzhang.net/./papers/tunesensor-iswc.pdf
• http://wnzhang.net/./papers/camra-2011.pdf
• http://wnzhang.net/./papers/kddcup-2011.pdf
• http://wnzhang.net/./papers/fbmf.pdf
• http://wnzhang.net/./papers/loddo-jist.pdf
• http://wnzhang.net/./papers/lshtc.pdf
• Yahoo! Learning to Rank Challenge 2010

• DAI 2025, London
• https://hml.boyuai.com/
• https://hrl.boyuai.com/
• http://www.optimalrtb.com/cikm16/
• https://github.com/wnzhang/rtb-papers/
• https://github.com/sjtu-marl/malib
• https://github.com/huawei-noah/SMARTS
• https://github.com/cityflow-project/CityFlow
• https://github.com/geek-ai/MAgent
• https://github.com/geek-ai/Texygen/
• http://www.jmlr.org/papers/v13/chen12a.html
• Google Scholar
• https://arxiv.org/abs/2504.00587
• https://openreview.net/pdf/3daf9ed44ae87b47757d6f6628a7b096d0d1560e.pdf
• https://arxiv.org/abs/2507.16853
• https://arxiv.org/abs/2504.06020
• https://arxiv.org/abs/2505.18763
• https://arxiv.org/abs/2506.12851
• https://arxiv.org/abs/2503.09501
• https://arxiv.org/abs/2506.12704
• https://arxiv.org/abs/2502.16268
• https://neurips.cc/virtual/2025/poster/121939
• https://arxiv.org/abs/2409.09584
• https://arxiv.org/abs/2505.15356
• https://arxiv.org/abs/2505.13492
• https://arxiv.org/abs/2504.04706
• https://arxiv.org/abs/2410.11188
• https://arxiv.org/abs/2408.05676
• https://dl.acm.org/doi/abs/10.1145/3726302.3729885
• https://aclanthology.org/2025.acl-long.589/
• https://arxiv.org/abs/2502.11882
• https://aclanthology.org/2025.findings-acl.428/
• https://arxiv.org/abs/2502.14361
• https://arxiv.org/abs/2502.12492
• https://arxiv.org/abs/2412.16516
• https://dl.acm.org/doi/10.1145/3711896.3736554
• https://arxiv.org/abs/2412.18241
• https://arxiv.org/abs/2502.13539
• https://arxiv.org/abs/2412.10787
• https://arxiv.org/abs/2506.06033
• https://arxiv.org/abs/2502.12631
• https://www.arxiv.org/abs/2408.10520
• https://openreview.net/pdf?id=XMOaOigOQo
• https://openreview.net/pdf?id=Y8L5RB4GWb
• https://arxiv.org/abs/2410.04587
• https://dl.acm.org/doi/10.5555/3709347.3744042
• https://arxiv.org/abs/2402.02439
• https://arxiv.org/abs/2309.17179
• https://arxiv.org/abs/2403.06221
• https://arxiv.org/abs/2310.09234
• https://arxiv.org/abs/2308.11131
• https://arxiv.org/abs/2404.07581
• https://arxiv.org/abs/2401.12553
• https://link.springer.com/chapter/10.1007/978-981-97-2262-4_17
• https://dl.acm.org/doi/10.1145/3643685
• https://arxiv.org/abs/2311.01378
• https://arxiv.org/abs/2402.00348
• https://arxiv.org/abs/2305.09458
• https://arxiv.org/abs/2309.12951
• https://arxiv.org/abs/2210.05662
• https://arxiv.org/abs/2306.05064
• https://www.jmlr.org/papers/volume24/22-0169/22-0169.pdf
• https://www.jmlr.org/papers/volume24/22-0606/22-0606.pdf
• https://www.ijcai.org/proceedings/2023/0808.pdf
• https://openreview.net/attachment?id=elL6uw9qOX&name=pdf
• https://arxiv.org/abs/2306.04234
• https://www.microsoft.com/en-us/research/uploads/prod/2023/02/2023-AAAI-Learning-Decomposed-Spatial-Relations-for-Multi-Variate-Time-Series-Modeling.pdf
• https://arxiv.org/abs/2206.09328
• https://arxiv.org/abs/2302.06205
• https://arxiv.org/abs/2302.00965
• https://arxiv.org/abs/2203.16406
• https://arxiv.org/abs/2206.08569
• https://arxiv.org/abs/2205.14953
• https://arxiv.org/abs/2102.00714
• https://openreview.net/forum?id=7e6W6LEOBg3
• https://arxiv.org/abs/2207.13701
• https://arxiv.org/abs/2208.01889
• https://arxiv.org/abs/2203.02214
• https://arxiv.org/abs/2205.09284
• https://arxiv.org/abs/2201.08299
• https://arxiv.org/abs/2202.06602
• https://openreview.net/forum?id=daap2-CzSa
• https://openreview.net/forum?id=PTRo58zPt3P
• https://openreview.net/forum?id=VTNjxbFRKly
• https://arxiv.org/abs/2202.03097
• https://arxiv.org/abs/2202.04333
• https://arxiv.org/abs/2111.10476
• https://ieeexplore.ieee.org/document/9661309
• https://arxiv.org/abs/2111.03318
• https://arxiv.org/abs/2202.12481
• https://arxiv.org/abs/2111.08550
• https://arxiv.org/abs/2111.02056
• https://arxiv.org/abs/2111.05407
• https://www.cs.sjtu.edu.cn/~fu-ly/paper/GAKG.pdf
• https://arxiv.org/abs/2103.13355
• https://arxiv.org/abs/2011.12683
• https://2021.ecmlpkdd.org/wp-content/uploads/2021/07/sub_46.pdf
• https://2021.ecmlpkdd.org/wp-content/uploads/2021/07/sub_581.pdf
• https://arxiv.org/abs/2012.10171
• https://arxiv.org/abs/2108.05252
• https://arxiv.org/abs/2012.08986
• https://arxiv.org/abs/2108.07107
• https://arxiv.org/abs/2105.03363
• https://arxiv.org/abs/2105.06350
• https://arxiv.org/abs/2104.10584
• https://arxiv.org/abs/2008.07905
• https://ieeexplore.ieee.org/document/9432789
• https://arxiv.org/abs/2104.06077
• https://openreview.net/pdf?id=kHSu4ebxFXY
• https://proceedings.mlsys.org/paper/2021/file/8f14e45fceea167a5a36dedd4bea2543-Paper.pdf
• https://arxiv.org/abs/2004.09395
• http://proceedings.mlr.press/v130/guo21b/guo21b.pdf
• https://arxiv.org/abs/2103.10860
• https://arxiv.org/abs/2010.09776
• https://arxiv.org/abs/2010.09546
• https://arxiv.org/abs/2010.11737
• https://arxiv.org/abs/2007.01995
• https://arxiv.org/abs/2006.01482
• https://arxiv.org/abs/2009.08052
• https://arxiv.org/abs/2011.00550
• https://arxiv.org/pdf/2009.01453.pdf
• https://arxiv.org/abs/2007.00216
• https://arxiv.org/abs/2003.11235
• https://www.sciencedirect.com/science/article/abs/pii/S095070512030407X
• https://arxiv.org/abs/2005.14171
• https://arxiv.org/abs/2006.10389
• https://arxiv.org/abs/2004.14714
• https://www.ijcai.org/Proceedings/2020/0322.pdf
• https://www.ijcai.org/Proceedings/2020/0214.pdf
• https://www.ijcai.org/Proceedings/2020/0588.pdf
• https://arxiv.org/abs/2009.05991
• https://openreview.net/pdf?id=B1gZV1HYvS
• https://openreview.net/pdf?id=S1esMkHYPr
• https://arxiv.org/pdf/1909.03510.pdf
• https://arxiv.org/pdf/1908.05672.pdf
• https://arxiv.org/abs/2002.09803
• https://ieeexplore.ieee.org/document/8941296/
• https://arxiv.org/abs/1911.09310
• http://proceedings.mlr.press/v108/chen20a.html
• https://arxiv.org/pdf/1911.03883.pdf
• https://www.aclweb.org/anthology/D19-1313.pdf
• https://dl.acm.org/citation.cfm?id=3356464.3357706
• https://dl.acm.org/citation.cfm?id=3357707
• https://arxiv.org/abs/1905.05717
• https://arxiv.org/abs/1910.02591
• https://arxiv.org/abs/1905.11353
• https://arxiv.org/abs/1908.06698
• https://arxiv.org/abs/1809.03149
• https://arxiv.org/abs/1905.06933
• https://arxiv.org/abs/1804.03782
• https://arxiv.org/abs/1902.05687
• https://arxiv.org/abs/1903.01344
• https://arxiv.org/abs/1905.03028
• http://urban-computing.com/pdf/kdd_2019_camera_ready_TrajGuard.pdf
• https://arxiv.org/pdf/1908.04032.pdf
• https://arxiv.org/abs/1905.00758
• https://arxiv.org/abs/1906.01965
• https://arxiv.org/abs/1810.00143
• https://arxiv.org/abs/1901.06631
• https://arxiv.org/abs/1809.04234
• https://arxiv.org/abs/1811.05869
• https://arxiv.org/abs/1809.02403
• https://arxiv.org/abs/1808.03737
• https://arxiv.org/abs/1802.09756
• https://arxiv.org/abs/1802.05438
• https://arxiv.org/abs/1806.02639
• https://arxiv.org/pdf/1807.00311.pdf
• https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8306425
• https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8286891
• https://www.mdpi.com/1424-8220/18/4/1063
• https://arxiv.org/abs/1707.01310
• http://eprints.gla.ac.uk/166078/1/166078.pdf
• https://arxiv.org/abs/1703.02000
• https://rud.is/dl/ieee-sp-2018/435301a561.pdf
• https://arxiv.org/abs/1804.03396
• http://zhenghuiwang.net/files/naacl2018.pdf
• https://arxiv.org/abs/1709.08624
• https://arxiv.org/abs/1707.04873
• https://arxiv.org/abs/1711.08267
• http://xuejianwang.com/files/mlp.pdf
• https://arxiv.org/pdf/1707.01217.pdf
• http://ieeexplore.ieee.org/document/8115218/
• https://arxiv.org/abs/1702.06674
• http://apex.sjtu.edu.cn/public/files/papers/2017066/paper.pdf
• https://arxiv.org/abs/1705.10513
• https://arxiv.org/abs/1610.03013
• http://people.dbmi.columbia.edu/noemie/papers/17www_bc.pdf
• http://people.dbmi.columbia.edu/noemie/papers/17www_asd.pdf
• https://arxiv.org/abs/1609.05473
• https://arxiv.org/pdf/1611.00144.pdf
• http://apex.sjtu.edu.cn/public/files/papers/20160817/opt-ctr-bid.pdf
• http://apex.sjtu.edu.cn/public/files/members/20160817/functional-bid-lands.pdf
• http://discovery.ucl.ac.uk/1496878/1/weinan-zhang-phd-2016.pdf
• https://arxiv.org/pdf/1606.06905.pdf
• Data analysis and benchmarking paper
• MediaGamma Limited
• Microsoft Research Cambridge
• Google Inc.
• Digital Enterprise Research Institute
• Microsoft Research Asia
• AceKG Academic Knowledge Graph
• Data description and benchmarking paper
• iPinYou RTB Ad Logs
• CrunchBase Venture Capital Investments
• iPinyou DSP 2013
• CAMERa 2011
• KDD Cup 2011
• LSHTC 2009
• Statcounter
• http://statcounter.com/free-hit-counter/
• 2nd Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2020
• SIGIR 2020 Workshop on Deep Reinforcement Learning for Information Retrieval

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