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 Sheng Gao

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Average citations per article5.07
Citation Count76
Publication count15
Publication years2003-2015
Available for download7
Average downloads per article539.29
Downloads (cumulative)3,775
Downloads (12 Months)127
Downloads (6 Weeks)12
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15 results found Export Results: bibtexendnoteacmrefcsv

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1 published by ACM
October 2015 MM '15: Proceedings of the 23rd ACM international conference on Multimedia
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 2,   Downloads (12 Months): 19,   Downloads (Overall): 81

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Content representation of music signal is an essential part of music information retrieval applications, e.g. chorus detection, genre classification, etc. In the paper, we propose the octave-dependent probabilistic latent semantic analysis (OdPlsa) to discover the latent audio patterns (or clusters) through spectral-temporal analysis. Then the audio content of each segment ...
Keywords: chorus detection, chroma, probabilistic latent semantic analysis

2 published by ACM
August 2013 ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Publisher: ACM
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 2,   Downloads (12 Months): 15,   Downloads (Overall): 122

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In this paper, we propose a new framework for opinion summarization based on sentence selection. Our goal is to assist users to get helpful opinion suggestions from reviews by only reading a short summary with few informative sentences, where the quality of summary is evaluated in terms of both aspect ...

3 published by ACM
October 2011 CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 1,   Downloads (12 Months): 22,   Downloads (Overall): 496

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Sentiment classification is becoming attractive in recent years because of its potential commercial applications. It exploits supervised learning methods to learn the classifiers from the annotated training documents. The challenge in sentiment classification lies in that the sentiment domains are diverse, heterogeneous and fast-growing. The classifiers trained on one domain ...
Keywords: domain adaptation, sentiment classification, latent topic analysis, opinion mining

4
January 2011 MMM'11: Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

In this paper we present a learning algorithm to estimate a risksensitive and document-relation embedded ranking function so that the ranking score can reflect both the query-document relevance degree and the risk of estimating relevance when the document relation is considered. With proper assumptions, an analytic form of the ranking ...
Keywords: diversity search, language model, risk minimization

5
November 2009 ICIP'09: Proceedings of the 16th IEEE international conference on Image processing
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

To have a robust and informative image content representation for image categorization, we often need to extract as many as possible visual features at various locations, scales and orientations. Thus it is not surprised that an image has a few hundreds or even thousands of visual descriptors. This raises huge ...
Keywords: Markov chain, classification accuracy, sample selection, scene recognition, pagerank

6
October 2008 Pattern Recognition: Volume 41 Issue 10, October, 2008
Publisher: Elsevier Science Inc.
Bibliometrics:
Citation Count: 4

A generalized discriminative multiple instance learning (GDMIL) algorithm is presented to train the classifier in the condition of vague annotation of training samples GDMIL not only inherits the original MIL's capability of automatically weighting the instances in the bag according to their relevance to the concept but also integrates generative ...
Keywords: Multiple instance learning, Discriminative training, Semantic concept detection, Area under the ROC curve, Classification accuracy

7
November 2007 IEEE Transactions on Multimedia: Volume 9 Issue 7, November 2007
Publisher: IEEE Press
Bibliometrics:
Citation Count: 4

In this paper, a kernel-based learning algorithm, kernel rank, is presented for improving the performance of semantic concept detection. By designing a classifier optimizing the receiver operating characteristic (ROC) curve using kernel rank, we provide a generic framework to optimize any differentiable ranking function using effective smoothing functions. kernel rank ...
Keywords: multimedia database, semantic concept detection, Area under ROC, ROC curve, information retrieval

8 published by ACM
September 2007 MM '07: Proceedings of the 15th ACM international conference on Multimedia
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 4,   Downloads (Overall): 240

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Given the rich content-based features of multimedia (e.g., visual, text, or audio) and the development of various approaches to automatic detectors (e.g., SVM, Adaboost, HMM or GMM, etc), can we find an efficient approach to combine these evidences? In the paper, we address this issue by proposing an Integrated Statistical ...
Keywords: average precision, evidence fusion, model-based fusion, semantic concept detection

9
August 2006 ICPR '06: Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 3

An ensemble learning framework is proposed to optimize the receiver operating characteristic (ROC) curve corresponding to a given classifier. The proposed ensemble maximal figure-ofmerit (E-MFoM) learning framework meets four key requirements desirable for ROC optimization, namely: (1) each classifier in the ensemble can be learned with any specified performance metric ...

10
August 2006 ICPR '06: Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

With the proliferation of camera phones, new information retrieval applications will emerge. The image of a scene captured by a camera phone can be a query to a remote server to identify the scene and return relevant information. But unconstrained scene identification is an open problem. In this paper, we ...

11
July 2006 CIVR'06: Proceedings of the 5th international conference on Image and Video Retrieval
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 10

We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept structures in images. Characterizing image concepts by mixture models is one of the most effective techniques in automatic image annotation (AIA) for concept-based image retrieval. However it also ...

12 published by ACM
April 2006 ACM Transactions on Information Systems (TOIS): Volume 24 Issue 2, April 2006
Publisher: ACM
Bibliometrics:
Citation Count: 9
Downloads (6 Weeks): 2,   Downloads (12 Months): 18,   Downloads (Overall): 841

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We propose a maximal figure-of-merit (MFoM)-learning approach for robust classifier design, which directly optimizes performance metrics of interest for different target classifiers. The proposed approach, embedding the decision functions of classifiers and performance metrics into an overall training objective, learns the parameters of classifiers in a decision-feedback manner to effectively ...
Keywords: Text categorization, generalized probabilistic descent method, information retrieval, decision tree, latent semantic indexing, maximal figure-of-merit

13
August 2004 ICPR '04: Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

In this paper a musical event based indexing approach is proposed and its application to content-based music identification is studied. The events, which function as term words used in text retrieval or basic speech units in speech recognition, are inferred using an unsupervised learning algorithm. Its differences with the existing ...

14 published by ACM
July 2004 ICML '04: Proceedings of the twenty-first international conference on Machine learning
Publisher: ACM
Bibliometrics:
Citation Count: 23
Downloads (6 Weeks): 4,   Downloads (12 Months): 29,   Downloads (Overall): 788

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We propose a multiclass (MC) classification approach to text categorization (TC). To fully take advantage of both positive and negative training examples, a maximal figure-of-merit (MFoM) learning algorithm is introduced to train high performance MC classifiers. In contrast to conventional binary classification, the proposed MC scheme assigns a uniform score ...

15 published by ACM
July 2003 SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 15
Downloads (6 Weeks): 1,   Downloads (12 Months): 20,   Downloads (Overall): 1,207

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A novel maximal figure-of-merit (MFoM) learning approach to text categorization is proposed. Different from the conventional techniques, the proposed MFoM method attempts to integrate any performance metric of interest (e.g. accuracy, recall, precision, or F1 measure) into the design of any classifier. The corresponding classifier parameters are learned by optimizing ...
Keywords: decision tree, latent semantic indexing, support vector machines, maximal figure-of-merit, text categorization, generalized probabilistic descent method



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