@article{zhu08:_featur_selec_for_gene_expres,
author = {Shenghuo Zhu and Dingding Wang and Kai Yu and Tao Li
and Yihong Gong},
title = { Feature Selection for Gene Expression using
Model-based Entropy},
journal = {IEEE/ACM Transactions on Computational Biology and
Bioinformatics},
year = 2010,
volume = 7,
number = 1,
doi = {10.1109/TCBB.2008.35},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
code = {http://www.nec-labs.com/~zsh/files/FS-1.19.zip}
}
@inproceedings{yang10:_direc_networ_commun_detec,
author = {Tianbao Yang and Yun Chi and Shenghuo Zhu and Rong
Jin},
title = {Directed Network Community Detection: A Popularity
and Productivity Link Model },
booktitle = {SDM'10: Proceedings of the 2010 SIAM International
Conference On Data Mining},
year = 2010,
note = {to appear}
}
@inproceedings{guo09:_knowl_discov_citat_networ,
title = {Knowledge Discovery from Citation Networks},
author = {Zhen Guo and Zhongfei Zhang and Shenghuo Zhu and Yun
Chi and Yihong Gong},
booktitle = {ICDM '09: Ninth IEEE International Conference on
Data Mining},
year = 2009,
preprint = {http://www.nec-labs.com/~zsh/dm917_guo.pdf}
}
@article{wang09:_resol_enhan_learn_spars_assoc_image_patch,
title = {Resolution enhancement based on learning the sparse
association of image patches},
journal = {Pattern Recognition Letters},
volume = 31,
number = 1,
pages = {1 - 10},
year = 2010,
issn = {0167-8655},
doi = {10.1016/j.patrec.2009.09.004},
author = {Jinjun Wang and Shenghuo Zhu and Yihong Gong},
keywords = {Image super-resolution, Image representation,
Sparse-coding}
}
@inproceedings{1646276,
author = {Dingding Wang and Shenghuo Zhu and Tao Li and Yihong
Gong},
title = {Comparative document summarization via
discriminative sentence selection},
booktitle = {CIKM '09: Proceeding of the 18th ACM conference on
Information and knowledge management},
year = {2009},
isbn = {978-1-60558-512-3},
pages = {1963--1966},
location = {Hong Kong, China},
doi = {10.1145/1645953.1646276},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1639721,
author = {Sarah K. Taylor and Shenghuo Zhu and Yun Chi and Yi
Zhang},
title = {Ordering innovators and laggards for product
categorization and recommendation},
booktitle = {RecSys '09: Proceedings of the third ACM conference
on Recommender systems},
year = {2009},
isbn = {978-1-60558-435-5},
pages = {29--36},
location = {New York, New York, USA},
doi = {10.1145/1639714.1639721},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{wang09:_multi_docum_summar_using_senten,
author = {Dingding Wang and Shenghuo Zhu and Tao Li and Yihong
Gong },
title = {Multi-Document Summarization using Sentence-based
Topic Models},
booktitle = {ACL-IJCNLP '09: Joint conference of the 47th Annual
Meeting of the Association for Computational
Linguistics and the 4th International Joint
Conference on Natural Language Processing of the
Asian Federation of Natural Language Processing},
year = 2009,
url = {http://www.aclweb.org/anthology/P/P09/P09-2075.pdf}
}
@inproceedings{1571979,
author = {Kai Yu and Shenghuo Zhu and John Lafferty and Yihong
Gong},
title = {Fast Nonparametric Matrix Factorization for
Large-sale Collaborative Filtering },
booktitle = {SIGIR '09: Proceedings of the 32nd annual
international ACM SIGIR conference on Research and
development in information retrieval},
isbn = {978-1-60558-483-6},
pages = {211--218},
location = {Boston, MA, USA},
doi = {10.1145/1571941.1571979},
publisher = {ACM},
address = {New York, NY, USA},
year = 2009,
code = {mailto:kyu@sv.nec-labs.com}
}
@inproceedings{1572095,
author = {Zhen Guo and Shenghuo Zhu and Yun Chi and Zhongfei
Zhang and Yihong Gong},
title = {A Latent Topic Model for Linked Documents},
booktitle = {SIGIR '09: Proceedings of the 32nd annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = 2009,
isbn = {978-1-60558-483-6},
pages = {720--721},
location = {Boston, MA, USA},
doi = {10.1145/1571941.1572095},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{yang09:_bayes_framew_for_commun_detec,
author = {Tianbao Yang and Rong Jin and Yun Chi and Shenghuo
Zhu},
title = {A {Bayesian} Framework for Community Detection
Integrating Content and Link },
booktitle = {UAI '09: Proceedings of the 25th Conference on
Uncertainty in Artificial Intelligence},
year = 2009,
url = {http://www.cs.mcgill.ca/~uai2009/papers/UAI2009_0069_bbacda16c2951fd1d73e591f45141a67.pdf}
}
@inproceedings{1553525,
author = {Yu, Kai and Lafferty, John and Zhu, Shenghuo and
Gong, Yihong},
title = {Large-scale collaborative prediction using a
nonparametric random effects model},
booktitle = {ICML '09: Proceedings of the 26th Annual
International Conference on Machine Learning},
year = {2009},
isbn = {978-1-60558-516-1},
pages = {1185--1192},
location = {Montreal, Quebec, Canada},
doi = {10.1145/1553374.1553525},
publisher = {ACM},
address = {New York, NY, USA},
code = {mailto:kyu@sv.nec-labs.com}
}
@inproceedings{1557120,
author = {Yang, Tianbao and Jin, Rong and Chi, Yun and Zhu,
Shenghuo},
title = {Combining link and content for community detection:
a discriminative approach},
booktitle = {KDD '09: Proceedings of the 15th ACM SIGKDD
international conference on Knowledge discovery and
data mining},
year = {2009},
isbn = {978-1-60558-495-9},
pages = {927--936},
location = {Paris, France},
publisher = {ACM},
address = {New York, NY, USA},
doi = {10.1145/1557019.1557120},
slides = {http://www.nec-labs.com/~zsh/kdd09-slides.pdf}
}
@inproceedings{5202645,
author = {Jinjun Wang and Shenghuo Zhu and Yihong Gong},
title = {Resolution-Invariant Image Representation for
Content-based Zooming},
booktitle = {ICME '09: IEEE International Conference on
Multimedia and Expo},
year = 2009,
month = {28 2009-July 3},
volume = {},
number = {},
pages = {918-921},
keywords = {image representation, image resolution2D image
interpolation algorithm, content-based zooming,
example-based resolution enhancement, image quality,
image upscaling task, multiresolution bases set,
resolution-invariant image representation},
doi = {10.1109/ICME.2009.5202645},
issn = {1945-7871}
}
@inproceedings{5206679,
author = {Jinjun Wang and Shenghuo Zhu and Yihong Gong},
title = {Resolution-Invariant Image Representation and Its
Applications},
booktitle = {CVPR'09: IEEE Conference on Computer Vision and
Pattern Recognition},
year = {2009},
month = {June},
volume = {},
number = {},
pages = {2512-2519},
abstract = {We present a resolution-invariant image
representation (RIIR) framework in this paper. The
RIIR framework includes the methods of building a
set of multi-resolution bases from training images,
estimating the optimal sparse resolution-invariant
representation of any image, and reconstructing the
missing patches of any resolution level. As the
proposed RIIR framework has many potential
resolution enhancement applications, we discuss
three novel image magnification applications in this
paper. In the first application, we apply the RIIR
framework to perform Multi-Scale Image Magnification
where we also introduced a training strategy to
built a compact RIIR set. In the second application,
the RIIR framework is extended to conduct Continuous
Image Scaling where a new base at any resolution
level can be generated using existing RIIR set on
the fly. In the third application, we further apply
the RIIR framework onto Content-Base Automatic
Zooming applications. The experimental results show
that in all these applications, our RIIR based
method outperforms existing methods in various
aspects.},
keywords = {image enhancement, image reconstruction, image
representation, image resolutioncontent-base
automatic zooming application, continuous image
scaling, image magnification application,
multiresolution base, multiscale image
magnification, patch reconstruction, resolution
enhancement application, resolution-invariant image
representation, training strategy},
doi = {10.1109/CVPRW.2009.5206679},
issn = {1063-6919}
}
@article{yun09:_iolap,
author = {Yun Chi and Shenghuo Zhu and Koji Hino and Yihong
Gong and Yi Zhang},
title = {{iOLAP}: A Framework for Analyzing the Internet,
Social Networks, and Other Networked Data},
journal = {IEEE Transactions on Multimedia},
year = 2009,
month = {Apr},
volume = {11},
number = {3},
pages = {372--382},
doi = {10.1109/TMM.2009.2012912}
}
@article{li08:_music_clust_with_featur_from,
author = {Tao Li and Mitsunori Ogihara and Wei Peng and Bo
Shao and Shenghuo Zhu},
title = {Music Clustering with Features from Different
Information Sources},
journal = {IEEE Transactions on Multimedia},
year = 2009,
month = {Apr},
volume = {11},
number = {3},
pages = {477--485},
doi = {10.1109/TMM.2009.2012942}
}
@article{liu08:_visual_qualit_optim_super_resol,
author = {Feng Liu and Jinjun Wang and Shenghuo Zhu and
Michael Gleicher and Yihong Gong},
title = {Visual-Quality Optimizing Super Resolution},
journal = {Computer Graphics Forum},
year = 2009,
month = {Feb},
volume = 28,
number = 1,
pages = {127--140},
publisher = {The Eurographics Association and Blackwell
Publishing Ltd.},
doi = {10.1111/j.1467-8659.2008.01305.x}
}
@inproceedings{lin09:_learn_spars_markov_networ_struc,
author = {Yuanqing Lin and Shenghuo Zhu and Daniel Lee and Ben
Taskar},
title = {Learning Sparse Markov Network Structure via
Ensemble-of-Trees Models},
booktitle = {AISTAT'09: The Proceedings of the Twelfth
International Conference on Artificial Intelligence
and Statistics},
year = 2009,
volume = {5},
pages = {360--367},
url = {http://jmlr.csail.mit.edu/proceedings/papers/v5/lin09a/lin09a.pdf}
}
@inproceedings{yang09:_bayes_approac_towar_findin_commun,
author = {Tianbao Yang and Yun Chi and Shenghuo Zhu and Yihong
Gong and Rong Jin},
title = {A {Bayesian} Approach Toward Finding Communities and
Their Evolutions in Dynamic Social Networks},
booktitle = {SDM'09: Proceedings of the 2009 SIAM International
Conference On Data Mining},
year = 2009,
pages = {990--1001},
slides = {http://www.nec-labs.com/~zsh/sdm2009-slides.pdf},
url = {http://www.siam.org/proceedings/datamining/2009/dm09_090_yangt.pdf}
}
@article{1514891,
author = {Yu-Ru Lin and Yun Chi and Shenghuo Zhu and Hari
Sundaram and Belle L. Tseng},
title = {Analyzing communities and their evolutions in
dynamic social networks},
journal = {ACM Trans. Knowl. Discov. Data},
volume = {3},
number = {2},
year = {2009},
issn = {1556-4681},
pages = {1--31},
doi = {10.1145/1514888.1514891},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{NIPS2008_0664,
author = {Shenghuo Zhu and Kai Yu and Yihong Gong},
title = {Stochastic Relational Models for Large-scale Dyadic
Data using {MCMC}},
booktitle = {NIPS '08: Advances in Neural Information Processing
Systems 21},
publisher = {MIT Press},
address = {Cambridge, MA},
editor = {D. Koller and D. Schuurmans and Y. Bengio and
L. Bottou},
pages = {1993--2000},
year = 2009,
url = {http://books.nips.cc/papers/files/nips21/NIPS2008_0664.pdf},
code = {http://www.nec-labs.com/~zsh/files/BSRM-1.18.zip},
data = {http://www.nec-labs.com/~zsh/files/eachmovie_80.mat}
}
@article{1540293,
author = {Ding, Chris and Li, Tao and Zhu, Shenghuo},
title = {{KDD2008} workshop report {DMMT'08}: data mining using
matrices and tensors},
journal = {SIGKDD Explor. Newsl.},
volume = {10},
number = {2},
year = {2008},
issn = {1931-0145},
pages = {54--56},
doi = {10.1145/1540276.1540293},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1459467,
author = {Liu,, Feng and Wang,, Jinjun and Zhu,, Shenghuo and
Gleicher,, Michael and Gong,, Yihong},
title = {Noisy video super-resolution},
booktitle = {MM '08: Proceeding of the 16th ACM international
conference on Multimedia},
year = {2008},
isbn = {978-1-60558-303-7},
pages = {713--716},
location = {Vancouver, British Columbia, Canada},
doi = {10.1145/1459359.1459467},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1458206,
author = {Yun Chi and Shenghuo Zhu and Yihong Gong and Yi
Zhang},
title = {Probabilistic Polyadic Factorization and Its
Application to Personalized Recommendation},
booktitle = {CIKM '08: Proceedings of the 17th ACM Conference on
Information and Knowledge Management},
year = 2008,
pages = {941--950},
isbn = {978-1-59593-991-3},
location = {Napa Valley, California, USA},
doi = {10.1145/1458082.1458206},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1458319,
author = {Dingding Wang and Shenghuo Zhu and Yun Chi and Tao
Li},
title = {Integrating Clustering and Multi-Document
Summarization to Improve Document Understanding},
booktitle = {CIKM '08: Proceedings of the 17th ACM Conference on
Information and Knowledge Management},
isbn = {978-1-59593-991-3},
pages = {1435--1436},
location = {Napa Valley, California, USA},
year = 2008,
doi = {10.1145/1458082.1458319},
publisher = {ACM},
address = {New York, NY, USA},
code = {http://www.nec-labs.com/~zsh/files/LCA-1.19.zip}
}
@inproceedings{1453937,
author = {Shenghuo Zhu and Tao Li and Zhiyuan Chen and
Dingding Wang and Yihong Gong},
title = {Dynamic active probing of helpdesk databases},
booktitle = {VLDB '08: Proceedings of the 34th International
Conference on Very Large Data Bases},
year = {2008},
pages = {748--760},
doi = {10.1145/1453856.1453937},
url = {http://doi.acm.org/10.1145/1453856.1453937},
publisher = {VLDB Endowment}
}
@inproceedings{1390442,
author = {Kai Yu and Shenghuo Zhu and Wei Xu and Yihong Gong},
title = {Non-greedy active learning for text categorization
using convex ansductive experimental design},
booktitle = {SIGIR '08: Proceedings of the 31st annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = {2008},
isbn = {978-1-60558-164-4},
pages = {635--642},
location = {Singapore, Singapore},
doi = {10.1145/1390334.1390442},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1390387,
author = {Dingding Wang and Tao Li and Shenghuo Zhu and Chris
Ding},
title = {Multi-document summarization via sentence-level
semantic analysis and symmetric matrix
factorization},
booktitle = {SIGIR '08: Proceedings of the 31st annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = {2008},
isbn = {978-1-60558-164-4},
pages = {307--314},
location = {Singapore, Singapore},
doi = {10.1145/1390334.1390387},
publisher = {ACM},
address = {New York, NY, USA}
}
@article{li08:_text_categ_via_gener_discr_analy,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Text Categorization via Generalized Discriminant
Analysis},
journal = {Information Processing and Management},
year = 2008,
doi = {10.1016/j.ipm.2008.03.005},
pages = {1684--1697},
volume = 44,
number = 5,
publisher = {Elsevier Ltd.}
}
@inproceedings{li01:_minin_patter_from_case_base_analy,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Mining Patterns from Case Base Analysis},
booktitle = {Workshop on Integrating Data Mining and Knowledge
Management},
address = {San Jose, CA},
year = 2001,
url = {http://cui.unige.ch/~hilario/icdm-01/DM-KM-Final/Zhu.ps}
}
@inproceedings{1250984,
title = {Using discriminant analysis for multi-class
classification},
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
booktitle = {ICDM '03: Third IEEE International Conference on
Data Mining},
year = {2003},
month = {Nov.},
volume = {},
number = {},
pages = {589-592},
abstract = {Discriminant analysis is known to learn
discriminative feature transformations. We study its
use in multiclass classification problems. The
performance is tested on a large collection of
benchmark datasets.},
keywords = { computational complexity, learning (artificial
intelligence), pattern classification, pattern
recognition, statistical databases, support vector
machines SVM, benchmark dataset collection,
discriminant analysis, discriminative feature
transformation, machine learning problem, multiclass
classification, support vector machine},
doi = {10.1109/ICDM.2003.1250984}
}
@inproceedings{679603,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara and
Yinhe Cheng},
title = {Estimating Joint Probabilities from Marginal Ones},
booktitle = {DaWaK: Proceedings of the 4th International
Conference on Data Warehousing and Knowledge
Discovery},
year = {2002},
isbn = {3-540-44123-9},
pages = {31--41},
publisher = {Springer-Verlag},
address = {London, UK},
editor = {Y. Kambayashi and W. Winiwarter and M. Arikawa},
volume = 2454,
series = {LNCS},
doi = {10.1007/3-540-46145-0_4}
}
@inproceedings{679607,
author = {Shenghuo Zhu and Tao Li and Mitsunori Ogihara},
title = {{CoFD}: An Algorithm for Non-distance Based
Clustering in High Dimensional Spaces},
booktitle = {DaWaK: Proceedings of the 4th International
Conference on Data Warehousing and Knowledge
Discovery},
year = {2002},
isbn = {3-540-44123-9},
pages = {52--62},
publisher = {Springer-Verlag},
address = {London, UK},
editor = {Y. Kambayashi and W. Winiwarter and M. Arikawa},
volume = 2454,
series = {LNCS},
doi = {10.1007/3-540-46145-0_6}
}
@article{1293871,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Algorithms for clustering high dimensional and
distributed data},
journal = {Intell. Data Anal.},
volume = {7},
number = {4},
year = {2003},
issn = {1088-467X},
pages = {305--326},
publisher = {IOS Press},
address = {Amsterdam, The Netherlands, The Netherlands},
url = {http://iospress.metapress.com/content/myp4du70v8ht0gp0}
}
@article{1293878,
author = {Tao Li and Mitsunori Ogihara and Shenghuo Zhu},
title = {Association-based similarity testing and its
applications},
journal = {Intell. Data Anal.},
volume = {7},
number = {3},
year = {2003},
issn = {1088-467X},
pages = {209--232},
publisher = {IOS Press},
address = {Amsterdam, The Netherlands, The Netherlands},
url = {http://iospress.metapress.com/content/7dgwwdfr9j6lyq9x}
}
@inproceedings{li05:_clust_binar_data,
author = {Tao Li and Shenghuo Zhu},
title = {On Clustering Binary Data},
booktitle = {SDM'05: Proceedings of the 2005 SIAM International
Conference On Data Mining},
pages = {526--530},
year = 2005,
url = {http://www.siam.org/proceedings/datamining/2005/dm05_54LiT.pdf}
}
@inproceedings{li05:_hierar_docum_class_using_autom_gener_hierar,
author = {Tao Li and Shenghuo Zhu},
title = {Hierarchical Document Classification Using
Automatically Generated Hierarchy},
booktitle = {SDM'05: Proceedings of the 2005 SIAM International
Conference On Data Mining},
pages = {521--525},
year = 2005,
url = {http://www.siam.org/proceedings/datamining/2005/dm05_53LiT.pdf}
}
@inproceedings{sia07:_captur_user_inter_by_both,
author = {Ka Cheung Sia and Shenghuo Zhu Yun Chi and Koji Hino and Belle L. Tseng},
title = {Capturing User Interests by Both Exploitation and
Exploration},
booktitle = {UM '07: Proceedings of User Modeling},
pages = {334-339},
year = 2007,
doi = {10.1007/978-3-540-73078-1_40}
}
@inproceedings{sia07:_monit_rss_feeds_based_user_brows_patter,
author = {Ka Cheung Sia and Junghoo Cho and Koji Hino and Yun Chi and Shenghuo Zhu and Belle L. Tseng},
title = { Monitoring {RSS} Feeds Based on User Browsing
Pattern},
booktitle = {ICWSM '07: International Conference on Weblogs and
Social Media},
year = 2007,
url = {http://www.icwsm.org/papers/2--Sia-Cho-Hino-Chi-Zhu-Tseng.pdf}
}
@inproceedings{zhang06:_trend_analy_for_large_docum_stream,
author = {Chengliang Zhang and Shenghuo Zhu and Yihong Gong},
title = {Trend Analysis for Large Document Streams},
booktitle = {ICMLA '06: Proceedings of the 5th International
Conference on Machine Learning and Applications},
year = 2006,
isbn = {0-7695-2735-3},
pages = {285--295},
doi = {10.1109/ICMLA.2006.51},
publisher = {IEEE Computer Society},
address = {Washington, DC, USA}
}
@inproceedings{zhu07:_combin_conten_and_link_for,
author = {Shenghuo Zhu and Kai Yu and Yun Chi and Yihong Gong},
title = {Combining content and link for classification using
matrix factorization},
booktitle = {SIGIR '07: Proceedings of the 30th annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = 2007,
isbn = {978-1-59593-597-7},
pages = {487--494},
location = {Amsterdam, The Netherlands},
doi = {10.1145/1277741.1277825},
publisher = {ACM Press},
address = {New York, NY, USA},
code = {http://www.nec-labs.com/~zsh/files/link-fact-1.18.zip},
data = {http://www.nec-labs.com/~zsh/files/link-fact-data.zip}
}
@inproceedings{1007510,
title = {A non-distance based clustering algorithm},
author = {Shenghuo Zhu and Tao Li},
booktitle = {IJCNN '02: Proceedings of the 2002 International
Joint Conference on Neural Networks},
year = {2002},
month = {},
volume = {3},
number = {},
pages = {2357-2362},
abstract = {The clustering problem has been widely studied since
it arises in many application domains. It aims at
identifying the distribution of patterns and
intrinsic correlations in large data sets by
partitioning the data points into similarity
clusters. Traditional clustering algorithms use
distance functions to measure similarity and are not
suitable for high dimensional spaces. In this paper,
we propose a non-distance based clustering algorithm
for high dimensional spaces. Based on the maximum
likelihood principle, the algorithm is to optimize
parameters to maximize the likelihood between data
points and the model generated by the
parameters. Experimental results on both synthetic
data sets and a real data set show the efficiency
and effectiveness of the algorithm},
keywords = {data mining, pattern clusteringapplication domains,
clustering algorithms, distance functions, intrinsic
correlations, large data sets, maximum likelihood
principle, nondistance based clustering algorithm,
real data set, similarity clusters},
doi = {10.1109/IJCNN.2002.1007510},
issn = {}
}
@inproceedings{1014138,
author = {Paat Rusmevichientong and Shenghuo Zhu and David
Selinger},
title = {Identifying early buyers from purchase data},
booktitle = {KDD '04: Proceedings of the tenth ACM SIGKDD
international conference on Knowledge discovery and
data mining},
year = {2004},
isbn = {1-58113-888-1},
pages = {671--677},
location = {Seattle, WA, USA},
doi = {10.1145/1014052.1014138},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1076082,
author = {Shenghuo Zhu and Xiang Ji and Wei Xu and Yihong
Gong},
title = {Multi-labelled classification using maximum entropy
method},
booktitle = {SIGIR '05: Proceedings of the 28th annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = {2005},
isbn = {1-59593-034-5},
pages = {274--281},
location = {Salvador, Brazil},
doi = {10.1145/1076034.1076082},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1148241,
author = {Xiang Ji and Wei Xu and Shenghuo Zhu},
title = {Document clustering with prior knowledge},
booktitle = {SIGIR '06: Proceedings of the 29th annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = {2006},
isbn = {1-59593-369-7},
pages = {405--412},
location = {Seattle, Washington, USA},
publisher = {ACM},
address = {New York, NY, USA},
doi = {10.1145/1148170.1148241}
}
@inproceedings{1167008,
author = {Chen Yu and Dana H. Ballard and Shenghuo Zhu},
title = {Attentional object spotting by integrating
multimodal input},
booktitle = {Proceedings. Fourth IEEE International Conference on
Multimodal Interfaces},
year = {2002},
month = {},
volume = {},
number = {},
pages = { 287-292},
abstract = { An intelligent human-computer interface is expected
to allow computers to work with users in a
cooperative manner. To achieve this goal, computers
need to be aware of user attention and provide
assistance without explicit user requests. Cognitive
studies of eye movements suggest that in
accomplishing well-learned tasks, the performer's
focus of attention is locked onto ongoing work and
more than 90% of eye movements are closely related
to the objects being manipulated in the tasks. In
light of this, we have developed an attentional
object spotting system that integrates multimodal
data consisting of eye position, head position and
video from the "first-person" perspective. To detect
the user's focus of attention, we modeled eye gaze
and head movements using a hidden Markov model (HMM)
representation. For each attentional point in time,
the object of user interest is automatically
extracted and recognized. We report the results of
experiments on finding attentional objects in the
natural task of "making a peanut-butter sandwich".},
keywords = { hidden Markov models, object detection, object
recognition, optical tracking, user interfaces,
video signal processing attentional object spotting
system, eye gaze, eye movement, eye position,
first-person perspective, head position, hidden
Markov model, intelligent human-computer interface,
multimodal data, multimodal input, user interest,
video},
doi = {10.1109/ICMI.2002.1167008},
issn = { }
}
@article{1177364,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Using discriminant analysis for multi-class
classification: an experimental investigation},
journal = {Knowl. Inf. Syst.},
volume = {10},
number = {4},
year = {2006},
issn = {0219-1377},
pages = {453--472},
doi = {10.1007/s10115-006-0013-y},
publisher = {Springer-Verlag New York, Inc.},
address = {New York, NY, USA}
}
@inproceedings{1182244,
title = {How well can wavelet denoising improve the accuracy
of computing fundamental matrices?},
author = {Qi Li and Tao Li and Shenghuo Zhu and Chandra Kambhamettu},
booktitle = {Proceedings. Workshop on Motion and Video Computing},
year = {2002},
month = {Dec.},
volume = {},
number = {},
pages = { 247-252},
abstract = { The existence of noise is a serious obstacle for
solving many computer vision problems. Computing the
fundamental matrix is a typical one. Motivated by
the success of the wavelet denoising technique in
image processing, we study the interesting topic of
how well wavelet denoising can improve the accuracy
of computing fundamental matrices. The answer
depends on: 1) what wavelets should be applied; 2)
what kind of images wavelets could be applied to in
order to improve the accuracy of their fundamental
matrix. Experimental results show that wavelet
denoising is promising in computer vision as well as
in image processing.},
keywords = { computer vision, image denoising, matrix algebra,
stereo image processing, wavelet transforms computer
vision, fundamental matrices, image processing,
stereo point correspondence, wavelet denoising},
doi = {10.1109/MOTION.2002.1182244},
issn = { }
}
@inproceedings{1184022,
title = {Improving medical/biological data classification
performance by wavelet preprocessing},
author = {Qi Li and Tao Li and Shenghuo Zhu and Chandra Kambhamettu},
booktitle = {ICDM '02: Proceedings IEEE International Conference
on Data Mining},
year = {2002},
month = {},
volume = {},
number = {},
pages = { 657-660},
abstract = { Many real-world datasets contain noise which could
degrade the performances of learning
algorithms. Motivated from the success of wavelet
denoising techniques in image data, we explore a
general solution to alleviate the effect of noisy
data by wavelet preprocessing for medical/biological
data classification. Our experiments are divided
into two categories: one is of different
classification algorithms on a specific database,
and the other is of a specific classification
algorithm (decision tree) on different
databases. The experiment results show that the
wavelet denoising of noisy data is able to improve
the accuracies of those classification methods, if
the localities of the attributes are strong enough.},
keywords = { data mining, learning (artificial intelligence),
medical computing, minimax techniques, noise,
pattern classification, wavelet transforms
biological data, data classification, datasets,
learning algorithms, medical data, minimax
threshold, noise, wavelet denoising, wavelet
preprocessing},
doi = {10.1109/ICDM.2002.1184022},
issn = { }
}
@inproceedings{1191120,
author = {Tao Li and Chengliang Zhang and Shenghuo Zhu},
title = {Empirical Studies on Multi-label Classification},
booktitle = {ICTAI '06: Proceedings of the 18th IEEE
International Conference on Tools with Artificial
Intelligence},
year = {2006},
isbn = {0-7695-2728-0},
pages = {86--92},
doi = {10.1109/ICTAI.2006.55},
publisher = {IEEE Computer Society},
address = {Washington, DC, USA}
}
@inproceedings{1281213,
author = {Yun Chi and Shenghuo Zhu and Xiaodan Song and
Junichi Tatemura and Belle L. Tseng},
title = {Structural and temporal analysis of the blogosphere
through community factorization},
booktitle = {KDD '07: Proceedings of the 13th ACM SIGKDD
international conference on Knowledge discovery and
data mining},
year = {2007},
isbn = {978-1-59593-609-7},
pages = {163--172},
location = {San Jose, California, USA},
doi = {10.1145/1281192.1281213},
publisher = {ACM},
address = {New York, NY, USA}
}
@article{1290890,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Hierarchical document classification using
automatically generated hierarchy},
journal = {J. Intell. Inf. Syst.},
volume = {29},
number = {2},
year = {2007},
issn = {0925-9902},
pages = {211--230},
doi = {10.1007/s10844-006-0019-7},
publisher = {Kluwer Academic Publishers},
address = {Hingham, MA, USA}
}
@inproceedings{1367517,
author = {Ding Zhou and Shenghuo Zhu and Kai Yu and Xiaodan
Song and Belle L. Tseng and Hongyuan Zha and C. Lee
Giles},
title = {Learning multiple graphs for document
recommendations},
booktitle = {WWW '08: Proceeding of the 17th international
conference on World Wide Web},
year = {2008},
isbn = {978-1-60558-085-2},
pages = {141--150},
location = {Beijing, China},
doi = {10.1145/1367497.1367517},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1367590,
author = {Yu-Ru Lin and Yun Chi and Shenghuo Zhu and Hari
Sundaram and Belle L. Tseng},
title = {Facetnet: a framework for analyzing communities and
their evolutions in dynamic networks},
booktitle = {WWW '08: Proceeding of the 17th international
conference on World Wide Web},
year = {2008},
isbn = {978-1-60558-085-2},
pages = {685--694},
location = {Beijing, China},
doi = {10.1145/1367497.1367590},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{1507501,
title = {Minimizing data exchange in ad hoc multi-robot
networks},
author = {Weihua Sheng and Qizhi Wang and Qingyan Yang and
Shenghuo Zhu},
booktitle = { ICAR '05: Proceedings 12th International Conference
on Advanced Robotics},
year = {2005},
month = {July},
volume = {},
number = {},
pages = {811-816},
abstract = {In many multi-robot applications, ad hoc networks
are formed for data communication, which enables
effective decision making and results in significant
energy and time saving. However, unnecessary large
volumes of communication data may still lead to big
time delay and energy waste. This paper addresses
the problem of how to reduce the data exchange among
multiple robots when they carry out cooperative area
exploration or coverage. In this application,
multiple robots need exchange map information in
order to minimize the repeated exploration or
coverage. When a connected ad hoc network can not be
maintained, the map data exchange or synchronization
should be carefully dealt with in order to reduce
the volume of data exchange. In this paper, a novel
sequence number-based map representation scheme and
an effective robot map update tracking scheme are
proposed. Based on them, an algorithm is developed
to reduce the volumes of map data exchange when
robot subnetworks merge. Simulation results validate
this algorithm},
keywords = {ad hoc networks, data communication, decision
making, delays, mobile robots, multi-robot systems,
synchronisationad hoc multirobot networks,
communication data, cooperative area exploration,
data communication, data exchange minimization, data
exchange reduction, decision making, exchange map
information, map data exchange, robot map update
tracking scheme, robot subnetworks, sequence
number-based map representation, synchronization,
time delay},
doi = {10.1109/ICAR.2005.1507501},
issn = {}
}
@inproceedings{1545195,
title = {Efficient map synchronization in ad hoc mobile robot
networks for environment exploration},
author = {Weihua Sheng and Qingyan Yang and Shenghuo Zhu and
Qizhi Wang},
booktitle = {IROS '05: IEEE/RSJ International Conference on
Intelligent Robots and Systems},
year = {2005},
month = {Aug.},
volume = {},
number = {},
pages = { 2297-2302},
abstract = { Information sharing through explicit communication
is necessary in many multi-robot applications in
order to achieve effective decision making. However,
unnecessary large volumes of communication data
usually lead to time delay and energy waste. This
paper addresses the problem of how to efficiently
synchronize the map (or explored area) among
multiple robots when they carry out cooperative area
exploration or coverage. In this application,
multiple robots need exchange map information in
order to minimize the repeated exploration or
coverage. When a connected ad hoc network can not be
maintained, the map synchronization problem becomes
more challenging. In this paper, a sequence number
based map representation scheme and an effective map
update tracking scheme are proposed. Based on them,
an algorithm is developed to reduce the volumes of
map exchange when robot subnetworks
merge. Simulation results validate this algorithm.},
keywords = { ad hoc networks, knowledge representation, mobile
computing, mobile robots, multi-robot systems ad hoc
mobile robot network, cooperative area exploration,
distributed algorithm, environment exploration, map
information exchange, map synchronization,
multirobot systems},
doi = {10.1109/IROS.2005.1545195},
issn = {}
}
@inproceedings{4053064,
title = {Integrating Features from Different Sources for
Music Information Retrieval},
author = {Tao Li and Mitsunori Ogihara and Shenghuo Zhu},
booktitle = {ICDM '06: Sixth International Conference on Data
Mining},
year = {2006},
month = {Dec. },
volume = {},
number = {},
pages = {372-381},
abstract = {Efficient and intelligent music information
retrieval is a very important topic of the 21st
century. With the ultimate goal of building personal
music information retrieval systems, this paper
studies the problem of identifying "similar" artists
using both lyrics and acoustic data. In this paper,
we present a clustering algorithm that integrates
features from both sources to perform bimodal
learning. The algorithm is tested on a data set
consisting of 570 songs from 53 albums of 41 artists
using artist similarity provided by All Music
Guide. Experimental results show that the accuracy
of artist similarity classifiers can be
significantly improved and that artist similarity
can be efficiently identified.},
doi = {10.1109/ICDM.2006.89},
issn = {1550-4786}
}
@inproceedings{4284695,
title = {Efficient Video Object Segmentation by Graph-Cut},
author = {Jinjun Wang and Wei Xu and Shenghuo Zhu and Yihong
Gong},
booktitle = {ICME '07: IEEE International Conference on
Multimedia and Expo},
year = {2007},
month = {July},
pages = {496-499},
abstract = {Segmentation of video objects from background is a
popular computer vision topic and has many important
applications. Most existing methods are either
computationally expensive or requiring manual
initialization, static cameras, and/or rigid
scenes. In a previous work, we proposed a joint
spatio-temporal linear regression algorithm to
automatically cluster the sparse edge/corner pixels
in each video frame and obtain two motion models for
the object and background respectively. To label the
rest pixels for object segmentation, in this paper,
we propose to model the Optical-Flow residual error,
color intensity residual error and temporal label
consistency features, as well as color/edge
orientation consistency constrains, in a graph, and
apply the Graph-Cut algorithm to minimize the energy
of the graph to obtain an optimal segmentation of
the two motion layers boundaries. Finally the object
layer is identified from the two using simple
heuristics. Experimental segmentation result with
videos taken by webcams is promising.},
keywords = {image colour analysis, image motion analysis, image
segmentation, regression analysis, video signal
processingcolor intensity residual error, computer
vision, graph-cut, motion layers boundaries,
spatio-temporal linear regression algorithm,
temporal label consistency features, video frame,
video object segmentation},
doi = {10.1109/ICME.2007.4284695}
}
@inproceedings{564411,
author = {Xin Liu and Yihong Gong and Wei Xu and Shenghuo Zhu},
title = {Document clustering with cluster refinement and
model selection capabilities},
booktitle = {SIGIR '02: Proceedings of the 25th annual
international ACM SIGIR conference on Research and
development in information retrieval},
year = {2002},
isbn = {1-58113-561-0},
pages = {191--198},
location = {Tampere, Finland},
doi = {10.1145/564376.564411},
publisher = {ACM},
address = {New York, NY, USA}
}
@article{772870,
author = {Tao Li and Qi Li and Shenghuo Zhu and Mitsunori
Ogihara},
title = {A survey on wavelet applications in data mining},
journal = {SIGKDD Explor. Newsl.},
volume = 4,
number = 2,
year = 2002,
issn = {1931-0145},
pages = {49--68},
doi = {10.1145/772862.772870},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{860531,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Topic hierarchy generation via linear discriminant
projection},
booktitle = {SIGIR '03: Proceedings of the 26th annual
international ACM SIGIR conference on Research and
development in informaion retrieval},
year = {2003},
isbn = {1-58113-646-3},
pages = {421--422},
location = {Toronto, Canada},
doi = {10.1145/860435.860531},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{952552,
author = {Tao Li and Shenghuo Zhu and Qi Li and Mitsunori
Ogihara},
title = {Gene functional classification by semi-supervised
learning from heterogeneous data},
booktitle = {SAC '03: Proceedings of the 2003 ACM symposium on
Applied computing},
year = {2003},
isbn = {1-58113-624-2},
pages = {78--82},
location = {Melbourne, Florida},
doi = {10.1145/952532.952552},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{952618,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {A new distributed data mining model based on
similarity},
booktitle = {SAC '03: Proceedings of the 2003 ACM symposium on
Applied computing},
year = {2003},
isbn = {1-58113-624-2},
pages = {432--436},
location = {Melbourne, Florida},
doi = {10.1145/952532.952618},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{952718,
author = {Qi Li and Chris Brown and Chandra Kambhamettu and
Tao Li and Shenghuo Zhu},
title = {A framework of individually-focused teleconferencing
{(IFT)} via an efficient 3D reprojection technique},
booktitle = {SAC '03: Proceedings of the 2003 ACM symposium on
Applied computing},
year = {2003},
isbn = {1-58113-624-2},
pages = {951--955},
location = {Melbourne, Florida},
doi = {10.1145/952532.952718},
publisher = {ACM},
address = {New York, NY, USA}
}
@inproceedings{956924,
author = {Tao Li and Shenghuo Zhu and Mitsunori Ogihara},
title = {Efficient multi-way text categorization via
generalized discriminant analysis},
booktitle = {CIKM '03: Proceedings of the twelfth international
conference on Information and knowledge management},
year = {2003},
isbn = {1-58113-723-0},
pages = {317--324},
location = {New Orleans, LA, USA},
doi = {10.1145/956863.956924},
publisher = {ACM},
address = {New York, NY, USA}
}
@incollection{NIPS2007_896,
title = {Predictive Matrix-Variate t Models},
author = {Shenghuo Zhu and Kai Yu and Yihong Gong},
booktitle = {NIPS '07: Advances in Neural Information Processing
Systems 20},
editor = {J.C. Platt and D. Koller and Y. Singer and
S. Roweis},
publisher = {MIT Press},
address = {Cambridge, MA},
pages = {1721--1728},
year = {2008},
url = {http://books.nips.cc/papers/files/nips20/NIPS2007_0896.pdf},
code = {http://www.nec-labs.com/~zsh/files/MVTM-1.18.zip},
data = {http://www.nec-labs.com/~zsh/files/eachmovie_80.mat}
}
@article{liu98:_align_senten_in_paral_corpor,
author = {Xin Liu and Ming Zhou and Shenghuo Zhu and Changning
Huang},
title = {Aligning sentences in parallel corpora using
self-extracted lexical information},
journal = {Chinese Journal of Computers},
year = 1998,
volume = {S1},
pages = {151--158},
url = {http://www.cnki.com.cn/Article/CJFDTotal-JSJX1998S1027.htm},
note = {in Chinese}
}
@article{zhu98:_effic_stoch_contex_free_parsin_algor,
author = {Shenghuo Zhu and Ming Zhou and Xin Liu and Changning
Huang},
title = {An efficient stochastic context-free parsing
algorithm},
journal = {Journal of Software},
year = 1998,
volume = 9,
number = 8,
pages = {592--597},
url = {http://www.cnki.com.cn/Article/CJFDTotal-RJXB808.005.htm},
note = {in Chinese}
}