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Travelled to:
1 × Brazil
1 × Canada
1 × Croatia
1 × Finland
1 × Israel
1 × Portugal
1 × United Kingdom
11 × USA
2 × Germany
3 × China
3 × France
Collaborated with:
E.P.Xing B.Zhang Z.Nie J.Wen N.Chen I.Sander A.Jantsch Z.J.Li N.Lao Y.Wang T.Shi Y.Tian S.Huang W.Ma S.Mei J.Zhu A.Zhang C.Li J.Chen M.Xu A.Ahmed X.Zhou Y.Liu H.Perkins X.Zheng L.Zhou X.Shi R.Cai L.Zhang Y.Shi J.Yan Y.Xiao W.Wang Y.Chen H.Tan H.Hon P.Colp M.Nanavati W.Aiello G.Coker T.Deegan P.Loscocco A.Warfield
Talks about:
margin (10) model (8) max (7) markov (6) topic (6) applic (5) bayesian (4) select (4) random (4) condit (4)

Person: Jun Zhu

DBLP DBLP: Zhu:Jun

Contributed to:

ICML 20152015
ICML c1 20142014
ICML c2 20142014
ICML c1 20132013
ICML c3 20132013
KDD 20132013
ICML 20122012
KDD 20122012
ICML 20112011
ICSM 20112011
KDD 20112011
SOSP 20112011
DATE 20102010
ICML 20102010
KDD 20102010
DATE 20092009
ICML 20092009
KDD 20092009
SAC 20092009
ICML 20082008
SAC 20082008
ESEC/FSE 20072007
ICML 20072007
KDD 20072007
KDD 20062006
ICML 20052005

Wrote 30 papers:

ICML-2015-WangZ #clustering #named #parametricity
DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics (YW, JZ), pp. 862–870.
ICML-c1-2014-MeiZZ #first-order #logic #modelling #robust
Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models (SM, JZ, JZ), pp. 253–261.
ICML-c1-2014-ShiZ #learning #online
Online Bayesian Passive-Aggressive Learning (TS, JZ), pp. 378–386.
ICML-c1-2014-ZhangZZ #infinity #markov #modelling
Max-Margin Infinite Hidden Markov Models (AZ, JZ, BZ), pp. 315–323.
ICML-c2-2014-LiZ0 #learning #multi
Bayesian Max-margin Multi-Task Learning with Data Augmentation (CL, JZ, JC), pp. 415–423.
ICML-c1-2013-ZhuCPZ #algorithm #modelling #performance #topic
Gibbs Max-Margin Topic Models with Fast Sampling Algorithms (JZ, NC, HP, BZ), pp. 124–132.
ICML-c3-2013-XuZZ #matrix #performance
Fast Max-Margin Matrix Factorization with Data Augmentation (MX, JZ, BZ), pp. 978–986.
KDD-2013-ZhuZZZ #modelling #scalability #topic
Scalable inference in max-margin topic models (JZ, XZ, LZ, BZ), pp. 964–972.
ICML-2012-Zhu #feature model #modelling #parametricity #predict
Max-Margin Nonparametric Latent Feature Models for Link Prediction (JZ), p. 154.
KDD-2012-TianZ #learning
Learning from crowds in the presence of schools of thought (YT, JZ), pp. 226–234.
ICML-2011-ZhuCX #infinity #kernel #process
Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines (JZ, NC, EPX), pp. 617–624.
ICSM-2011-HuangLZXW #approach #novel #testing
A novel approach to regression test selection for J2EE applications (SH, ZJL, JZ, YX, WW), pp. 13–22.
KDD-2011-ZhuLCX #performance #topic
Conditional topical coding: an efficient topic model conditioned on rich features (JZ, NL, NC, EPX), pp. 475–483.
SOSP-2011-ColpNZACDLW #security
Breaking up is hard to do: security and functionality in a commodity hypervisor (PC, MN, JZ, WA, GC, TD, PL, AW), pp. 189–202.
DATE-2010-ZhuSJ #configuration management #cpu #design #performance #streaming
Pareto efficient design for reconfigurable streaming applications on CPU/FPGAs (JZ, IS, AJ), pp. 1035–1040.
ICML-2010-ZhuX #random #topic
Conditional Topic Random Fields (JZ, EPX), pp. 1239–1246.
KDD-2010-ZhuLX #feature model #incremental #learning #markov #named #performance #random
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields (JZ, NL, EPX), pp. 303–312.
DATE-2009-ZhuSJ #architecture #cpu #hybrid #realtime #scheduling #streaming
Buffer minimization of real-time streaming applications scheduling on hybrid CPU/FPGA architectures (JZ, IS, AJ), pp. 1506–1511.
ICML-2009-ZhuAX #classification #modelling #named #topic
MedLDA: maximum margin supervised topic models for regression and classification (JZ, AA, EPX), pp. 1257–1264.
ICML-2009-ZhuX #markov #network #on the
On primal and dual sparsity of Markov networks (JZ, EPX), pp. 1265–1272.
KDD-2009-ShiZCZ #behaviour #online
User grouping behavior in online forums (XS, JZ, RC, LZ), pp. 777–786.
KDD-2009-ZhuXZ #markov #network
Primal sparse Max-margin Markov networks (JZ, EPX, BZ), pp. 1047–1056.
SAC-2009-HuangCZLT #java #testing
An optimized change-driven regression testing selection strategy for binary Java applications (SH, YC, JZ, ZJL, HT), pp. 558–565.
ICML-2008-ZhuXZ #markov #network
Laplace maximum margin Markov networks (JZ, EPX, BZ), pp. 1256–1263.
SAC-2008-ShiYLZ #composition #semantics #verification #web #web service
Path-based verification for composition of semantic web services (YS, JY, ZJL, JZ), pp. 2392–2396.
ESEC-FSE-2007-ZhouLZ #approach #model transformation
A segment-based approach for reconcilable model transformation (XZ, YL, JZ), pp. 517–520.
ICML-2007-ZhuNZW #markov #random #web
Dynamic hierarchical Markov random fields and their application to web data extraction (JZ, ZN, BZ, JRW), pp. 1175–1182.
KDD-2007-ZhuZNWH #approach #comprehension
Webpage understanding: an integrated approach (JZ, BZ, ZN, JRW, HWH), pp. 903–912.
KDD-2006-ZhuNWZM #detection #web
Simultaneous record detection and attribute labeling in web data extraction (JZ, ZN, JRW, BZ, WYM), pp. 494–503.
ICML-2005-ZhuNWZM #2d #information management #random #web
2D Conditional Random Fields for Web information extraction (JZ, ZN, JRW, BZ, WYM), pp. 1044–1051.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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