Travelled to:1 × Belgium
1 × France
1 × Germany
1 × Hungary
1 × Israel
1 × Italy
1 × South Africa
1 × The Netherlands
12 × USA
2 × United Kingdom
3 × China
5 × Canada
Collaborated with:I.King H.Ma H.Deng H.Yang H.Yang R.Jin Q.Zhang W.Zheng S.C.H.Hoi Z.Xu J.Song M.Cai Z.Zheng P.He S.He B.Li E.Y.Chang X.Cai S.C.Hoi S.Cai C.Rajaraman X.Xin T.Xie K.Huang J.Zhu D.Zhang G.Ling P.Garg X.Yu Z.Lin E.Yau S.K.S.Sze C.Gao J.Zeng D.L.0001 H.Yuan Z.Su S.Zhu C.Liu J.Zhu J.Han Y.Kang Y.Zhou H.Xu Z.Chen C.Cheng F.Xia T.Zhang R.Agrawal H.Huang X.Si J.Ye Z.Quan D.Huang X.Xia T.Lok Q.Fu H.Zhang C.Lin Q.Lin J.Lou H.Z.0002 X.X.0001 J.Liu
Talks about:learn (12) recommend (8) social (5) use (5) log (5) collabor (4) factor (4) model (4) imag (4) base (4)
Person: Michael R. Lyu
DBLP: Lyu:Michael_R=
Contributed to:
2015
2014
2013
2012
20112011
2011
2011
201120102010
2010201020092009
2009200920092008200720072006
20062006
20052004200420022002
1992
20022012
2016201820182019Wrote 53 papers:
- ICSE-v1-2015-ZhuHFZLZ #developer #learning
- Learning to Log: Helping Developers Make Informed Logging Decisions (JZ, PH, QF, HZ, MRL, DZ), pp. 415–425.
- RecSys-2014-ChengXZKL
- Gradient boosting factorization machines (CC, FX, TZ, IK, MRL), pp. 265–272.
- RecSys-2014-LingLK #approach #recommendation
- Ratings meet reviews, a combined approach to recommend (GL, MRL, IK), pp. 105–112.
- PLDI-2013-ZhangLYS #algorithm #alias #analysis #performance
- Fast algorithms for Dyck-CFL-reachability with applications to alias analysis (QZ, MRL, HY, ZS), pp. 435–446.
- CIKM-2012-GargKL #network #rating #social
- Information propagation in social rating networks (PG, IK, MRL), pp. 2279–2282.
- CIKM-2012-XinKALH #design #modelling
- Do ads compete or collaborate?: designing click models with full relationship incorporated (XX, IK, RA, MRL, HH), pp. 1839–1843.
- ASE-2011-ZhengMLXK #mining #testing #web
- Mining test oracles of web search engines (WZ, HM, MRL, TX, IK), pp. 408–411.
- CIKM-2011-LiKL #community
- Question routing in community question answering: putting category in its place (BL, IK, MRL), pp. 2041–2044.
- CIKM-2011-LiSLKC #identification #twitter
- Question identification on twitter (BL, XS, MRL, IK, EYC), pp. 2477–2480.
- CIKM-2011-YangZKL #how #learning #question #why
- Can irrelevant data help semi-supervised learning, why and how? (HY, SZ, IK, MRL), pp. 937–946.
- CIKM-2011-YuKL #approach #bidirectional #bottom-up #information management #top-down #towards
- Towards a top-down and bottom-up bidirectional approach to joint information extraction (XY, IK, MRL), pp. 847–856.
- ESEC-FSE-2011-ZhengZL #api #recommendation #using #web
- Cross-library API recommendation using web search engines (WZ, QZ, MRL), pp. 480–483.
- FASE-2011-ZhangZL #api #complexity #graph
- Flow-Augmented Call Graph: A New Foundation for Taming API Complexity (QZ, WZ, MRL), pp. 386–400.
- SIGIR-2011-MaLKL #modelling #probability #recommendation #web
- Probabilistic factor models for web site recommendation (HM, CL, IK, MRL), pp. 265–274.
- ASE-2010-ZhengZLX #generative #random #recommendation #sequence #testing
- Random unit-test generation with MUT-aware sequence recommendation (WZ, QZ, MRL, TX), pp. 293–296.
- CIKM-2010-YangKL #feature model #learning #multi #online
- Online learning for multi-task feature selection (HY, IK, MRL), pp. 1693–1696.
- ICML-2010-XuJYKL #kernel #learning #multi #performance
- Simple and Efficient Multiple Kernel Learning by Group Lasso (ZX, RJ, HY, IK, MRL), pp. 1175–1182.
- ICML-2010-YangXKL #learning #online
- Online Learning for Group Lasso (HY, ZX, IK, MRL), pp. 1191–1198.
- ICSE-2010-ZhengL #collaboration #predict #reliability
- Collaborative reliability prediction of service-oriented systems (ZZ, MRL), pp. 35–44.
- CIKM-2009-DengKL #retrieval #using
- Enhancing expertise retrieval using community-aware strategies (HD, IK, MRL), pp. 1733–1736.
- CIKM-2009-LinLK #named #novel #similarity
- MatchSim: a novel neighbor-based similarity measure with maximum neighborhood matching (ZL, MRL, IK), pp. 1613–1616.
- CIKM-2009-MaYKL #collaboration #consistency #matrix #statistics
- Semi-nonnegative matrix factorization with global statistical consistency for collaborative filtering (HM, HY, IK, MRL), pp. 767–776.
- CIKM-2009-XinKDL #framework #multi #random #recommendation #social
- A social recommendation framework based on multi-scale continuous conditional random fields (XX, IK, HD, MRL), pp. 1247–1256.
- ICML-2009-XuJYLK #feature model
- Non-monotonic feature selection (ZX, RJ, JY, MRL, IK), pp. 1145–1152.
- KDD-2009-DengLK #algorithm #graph
- A generalized Co-HITS algorithm and its application to bipartite graphs (HD, MRL, IK), pp. 239–248.
- RecSys-2009-MaLK #learning #recommendation #trust
- Learning to recommend with trust and distrust relationships (HM, MRL, IK), pp. 189–196.
- SIGIR-2009-DengKL #graph #modelling #query #representation
- Entropy-biased models for query representation on the click graph (HD, IK, MRL), pp. 339–346.
- SIGIR-2009-MaKL #learning #recommendation #social #trust
- Learning to recommend with social trust ensemble (HM, IK, MRL), pp. 203–210.
- CIKM-2008-MaYKL #learning #query #semantics
- Learning latent semantic relations from clickthrough data for query suggestion (HM, HY, IK, MRL), pp. 709–718.
- CIKM-2008-MaYLK #mining #network #process #social #using
- Mining social networks using heat diffusion processes for marketing candidates selection (HM, HY, MRL, IK), pp. 233–242.
- CIKM-2008-MaYLK08a #matrix #named #probability #recommendation #social #using
- SoRec: social recommendation using probabilistic matrix factorization (HM, HY, MRL, IK), pp. 931–940.
- CIKM-2008-XuJHLK #categorisation
- Semi-supervised text categorization by active search (ZX, RJ, KH, MRL, IK), pp. 1517–1518.
- ICML-2007-HoiJL #constraints #kernel #learning #matrix #parametricity
- Learning nonparametric kernel matrices from pairwise constraints (SCHH, RJ, MRL), pp. 361–368.
- SIGIR-2007-MaKL #collaboration #effectiveness #predict
- Effective missing data prediction for collaborative filtering (HM, IK, MRL), pp. 39–46.
- SIGIR-2007-YangKL #named #web
- DiffusionRank: a possible penicillin for web spamming (HY, IK, MRL), pp. 431–438.
- ICML-2006-HoiJZL #classification #image #learning
- Batch mode active learning and its application to medical image classification (SCHH, RJ, JZ, MRL), pp. 417–424.
- ICPR-v2-2006-QuanHXLL #analysis #online #verification
- Spectrum Analysis Based onWindows with Variable Widths for Online Signature Verification (ZHQ, DSH, XLX, MRL, TML), pp. 1122–1125.
- KDD-2006-HoiLC #classification #kernel #learning
- Learning the unified kernel machines for classification (SCHH, MRL, EYC), pp. 187–196.
- A-MOST-2005-CaiL #detection #fault #test coverage #testing
- The effect of code coverage on fault detection under different testing profiles (XC, MRL), pp. 84–90.
- ICML-2004-HuangYKL #classification #learning #scalability
- Learning large margin classifiers locally and globally (KH, HY, IK, MRL).
- ICPR-v3-2004-HoiL #feedback
- Group-based Relevance Feedback with Support Vector Machine Ensembles (SCHH, MRL), pp. 874–877.
- ICPR-v1-2002-SongCL #detection #image #performance
- Edge Color Distribution Transform: An Efficient Tool for ObjectDetection in Images (JS, MC, MRL), pp. 608–612.
- ICPR-v1-2002-SongCLC #approach #image #recognition #using
- A New Approach for Line Recognition in Large-size Images Using Hough Transform (JS, MC, MRL, SC), pp. 33–36.
- ICPR-v3-2002-SongCLC02a #image #recognition
- Graphics Recognition from Binary Images: One Step or Two Steps (JS, MC, MRL, SC), pp. 135–138.
- TOOLS-USA-1992-RajaramanL #c++ #metric #source code
- Some Coupling Measures for C++ Programs (CR, MRL), pp. 225–234.
- JCDL-2002-LyuYS #library #multimodal #video
- A multilingual, multimodal digital video library system (MRL, EY, SKSS), pp. 145–153.
- JCDL-2012-DengHLK #modelling #network #ranking
- Modeling and exploiting heterogeneous bibliographic networks for expertise ranking (HD, JH, MRL, IK), pp. 71–80.
- FSE-2016-KangZXL #android #named #performance
- DiagDroid: Android performance diagnosis via anatomizing asynchronous executions (YK, YZ, HX, MRL), pp. 410–421.
- ASE-2018-HeCHL #natural language
- Characterizing the natural language descriptions in software logging statements (PH, ZC, SH, MRL), pp. 178–189.
- ESEC-FSE-2018-GaoZ0LLK #named
- INFAR: insight extraction from app reviews (CG, JZ, DL0, CYL, MRL, IK), pp. 904–907.
- ESEC-FSE-2018-HeLLZLZ #analysis #identification #problem
- Identifying impactful service system problems via log analysis (SH, QL, JGL, HZ0, MRL, DZ), pp. 60–70.
- ASE-2019-GaoZX0LK #automation #generative #overview
- Automating App Review Response Generation (CG, JZ, XX0, DL0, MRL, IK), pp. 163–175.
- ASE-2019-LiuZHHZL #clustering #named
- Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression (JL, JZ, SH, PH, ZZ, MRL), pp. 863–873.