BibSLEIGH — Jun

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: Zhu:Jun

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

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.