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XHTML 1.0 W3C Rec
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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 DBLP: Lyu:Michael_R=

Contributed to:

ICSE 20152015
RecSys 20142014
PLDI 20132013
CIKM 20122012
ASE 20112011
CIKM 20112011
ESEC/FSE 20112011
FASE 20112011
SIGIR 20112011
ASE 20102010
CIKM 20102010
ICML 20102010
ICSE 20102010
CIKM 20092009
ICML 20092009
KDD 20092009
RecSys 20092009
SIGIR 20092009
CIKM 20082008
ICML 20072007
SIGIR 20072007
ICML 20062006
ICPR v2 20062006
KDD 20062006
A-MOST 20052005
ICML 20042004
ICPR v3 20042004
ICPR v1 20022002
ICPR v3 20022002
TOOLS USA 19921992
JCDL 20022002
JCDL 20122012
FSE 20162016
ASE 20182018
ESEC/FSE 20182018
ASE 20192019

Wrote 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.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.