Extracting Shared Subspace for Multi-label Classification (2009)
Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye
Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construct a binary...
Zhao Xu, Fraunhofer Iais, Shipeng Yu, Volker Tresp, Kai Yu
Social networks usually involve rich collections of objects, which are jointly linked into complex relational networks. Social network analysis has gained in importance due to the growing...
Probabilistic Interpretations and Extensions for a Family of 2D PCA-style Algorithms (2009)
Shipeng Yu, Jinbo Bi, Jieping Ye
Recently there have been several 2D or higher-order PCAstyle dimensionality reduction algorithms, but they mostly lack probabilistic interpretations and are difficult to apply with, e.g., incomplete...
Privacy-Preserving Cox Regression for Survival Analysis (2009)
Shipeng Yu, Glenn Fung, Romer Rosales, Sriram Krishnan, R. Bharat Rao, Cary Dehing-oberije
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we propose a...
Large Scale Diagnostic Code Classification for Medical Patient Records (2009)
Lucian Vlad Lita, Shipeng Yu, Stefan Niculescu, Jinbo Bi
A critical, yet not very well studied problem in medical applications is the issue of accurately labeling patient records according to diagnoses and procedures that patients have undergone. This...
Shipeng Yu, Balaji Krishnapuram, Romer Rosales, Harald Steck, R. Bharat Rao
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumptions of a large class...
Shipeng Yu, Balaji Krishnapuram, Romer Rosales, Harald Steck, R. Bharat Rao
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumptions of a large class...
Markus Bundschus, Shipeng Yu, Mathaeus Dejori, Volker Tresp
Statistical modeling of medical indexing processes for
Social networks usually involve rich collections of objects, which are jointly linked into complex relational networks. Social network analysis has gained in importance due to the growing...
Multi-Output Regularized Projection (2009)
Kai Yu, Shipeng Yu, Volker Tresp
Dimensionality reduction via feature projection has been widely used in pattern recognition and machine learning. It is often beneficial to derive the projections not only based on the inputs but...
ABSTRACT Multi-Label Informed Latent Semantic Indexing (2008)
Kai Yu, Shipeng Yu, Volker Tresp
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels) is available, it...
Computer-Aided Diagnosis Group, Siemens Medical Solutions, Malvern, PA (2008)
Jianwu Xu, Advisor Dr, Jose C. Principe, Advisors Drs, Shipeng Yu, Jinbo Bi, ...
Bayesian data analysis, learning with unlabeled data
Local Learning Projections (2008)
Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essentially seeks the...
Search and Retrieval—information filtering, retrieval models (2008)
Kai Yu, Volker Tresp, Shipeng Yu
Information filtering has made considerable progress in recent years.The predominant approaches are content-based methods and collaborative methods. Researchers have largely concentrated on either of...
Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, Harald Steck, R. Bharat Rao
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumptions of a large class...
Automatic Medical Coding of Patient Records via Weighted Ridge Regression (2008)
Jianwu Xu, Shipeng Yu, Jinbo Bi, Lucian Vlad Lita, Stefan Niculescu, R. Bharat Rao
In this paper, we apply weighted ridge regression to tackle the highly unbalanced data issue in automatic largescale ICD-9 coding of medical patient records. Since most of the ICD-9 codes are...
Large Scale Diagnostic Code Classification for Medical Patient Records (2008)
Lucian Vlad Lita, Shipeng Yu, Stefan Niculescu, Jinbo Bi
A critical, yet not very well studied problem in medical applications is the issue of accurately labeling patient records according to diagnoses and procedures that patients have undergone. This...
Hierarchy-Regularized Latent Semantic Indexing (2008)
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Volker Tresp, Hans-peter Kriegel
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. Beside textual features, the hierarchical structure of directories reflects additional and...
Deng Cai, Shipeng Yu, Ji-rong Wen, Wei-ying Ma
A new web content structure analysis based on visual representation is proposed in this paper. Many web applications such as information retrieval, information extraction and automatic page...
Shipeng Yu, Shipeng Yu, Supervisor Prof, Dr. Zuoquan Lin, Shipeng Yu
Directions: statistical machine learning for medical data mining
A Probabilistic Clustering-Projection Model for Discrete Data (2008)
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel
Abstract. For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a...
Local Learning Projections (2008)
Mingrui Wu, Kai Yu, Shipeng Yu, Bernhard Schölkopf
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essentially seeks the...
Siemens Medical Solutions, USA (2008)
Zhao Xu, Volker Tresp, Shipeng Yu, Kai Yu
of growing interest in machine learning. Xu et al. (2006) introduced the infinite hidden relational model
Hierarchy-Regularized Latent Semantic Indexing (2008)
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, Hans-peter Kriegel
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. The given class hierarchy does not only express the similarity between the classes, but can...
Multi-Output Regularized Projection (2008)
Kai Yu, Shipeng Yu, Volker Tresp
Dimensionality reduction via feature projection has been widely used in pattern recognition and machine learning. It is often beneficial to derive the projections not only based on the inputs but...
Dirichlet Enhanced Relational Learning (2008)
Zhao Xu, Kai Yu, Shipeng Yu, Hans-peter Kriegel
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be “personalized”, i.e., owned by entities or...
Robust Multi-Task Learning with t-Processes (2008)
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of “outlier ” tasks may greatly reduce overall system performance. We introduce a robust...
Dirichlet Enhanced Relational Learning (2008)
Zhao Xu, Kai Yu, Shipeng Yu, Hans-peter Kriegel
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be “personalized”, i.e., owned by entities or...
A Probabilistic Clustering-Projection Model for Discrete Data (2008)
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel
Abstract. For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a...
ABSTRACT Multi-Label Informed Latent Semantic Indexing (2008)
Kai Yu, Shipeng Yu, Volker Tresp
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels) is available, it...
Search and Retrieval—information filtering, retrieval models (2007)
Kai Yu, Volker Tresp, Shipeng Yu
Information filtering has made considerable progress in recent years. The predominant approaches are content-based methods and collaborative methods. Researchers have largely concentrated on either...
Stochastic relational models for discriminative link prediction (2007)
Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu
We introduce a Gaussian process (GP) framework, stochastic relational models (SRM), for learning social, physical, and other relational phenomena where interactions between entities are observed. The...
Stochastic relational models for discriminative link prediction (2007)
Kai Yu, Wei Chu, Shipeng Yu, Volker Tresp, Zhao Xu
We introduce a Gaussian process (GP) framework, stochastic relational models (SRM), for learning social, physical, and other relational phenomena where interactions between entities are observed. The...
Advanced Probabilistic Models for Clustering and Projection (2006)
Probabilistic modeling for data mining and machine learning problems is a fundamental research area. The general approach is to assume a generative model underlying the observed data, and estimate...
Advanced Probabilistic Models for Clustering and Projection (2006)
Probabilistic modeling for data mining and machine learning problems is a fundamental research area. The general approach is to assume a generative model underlying the observed data, and estimate...
Supervised probabilistic principal component analysis (2006)
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel, Mingrui Wu
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When labels of data are...
Supervised probabilistic principal component analysis (2006)
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel, Mingrui Wu
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When labels of data are...
Collaborative Ordinal Regression (2006)
Shipeng Yu, Kai Yu, Volker Tresp
Ordinal regression has become an effective way of learning user preferences, but most research focuses on single regression problems. In this paper we introduce collaborative ordinal regression,...
Supervised probabilistic principal component analysis (2006)
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel, Mingrui Wu
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When labels of data are...
Shipeng Yu, Prof Dr, Thomas Hofmann, ...
To my parents Probabilistic modeling for data mining and machine learning problems is a fundamental research area. The general approach is to assume a generative model underlying the observed data,...
Collaborative Ordinal Regression (2006)
Shipeng Yu, Kai Yu, Volker Tresp
Ordinal regression has become an effective way of learning user preferences, but most of research only focuses on single regression problem. In this paper we introduce collaborative ordinal...
Soft clustering on graphs (2005)
Kai Yu, Shipeng Yu, Volker Tresp
We propose a simple clustering framework on graphs that encode pairwise data similarities. Unlike usual similarity-based methods, the approach softly assigns data to clusters in a probabilistic way....
Blockwise supervised inference on large graphs (2005)
In this paper we consider supervised learning on large-scale graphs, which is highly demanding in terms of time and memory costs. We demonstrate that, if a graph has a bipartite structure that...
Blockwise supervised inference on large graphs (2005)
In this paper we consider supervised learning on large-scale graphs, which is highly demanding in terms of time and memory costs. We demonstrate that, if a graph has a bipartite structure that...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDMA) is introduced,...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-peter Kriegel
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDMA) is introduced,...
Soft clustering on graphs (2005)
Kai Yu, Shipeng Yu, Volker Tresp
We propose a simple clustering framework on graphs encoding pairwise data similarities. Unlike usual similarity-based methods, the approach softly assigns data to clusters in a probabilistic way....
Deng Cai, Shipeng Yu, Ji-rong Wen, Wei-ying Ma
Multiple-topic and varying-length of web pages are two negative factors significantly affecting the performance of web search. In this paper, we explore the use of page segmentation algorithms to...
Deng Cai, Shipeng Yu, Ji-rong Wen, Wei-ying Ma
Multiple-topic and varying-length of web pages are two negative factors significantly affecting the performance of web search. In this paper, we explore the use of page segmentation algorithms to...
Improving Pseudo-Relevance Feedback in Web Information Retrieval Using Web Page Segmentation (2003)
Yu, Shipeng, Cai, Deng, Wen, Ji-Rong, Ma, Wei-Ying
In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from...
Improving pseudo-relevance feedback in web information retrieval using web page segmentation (2003)
Shipeng Yu, Deng Cai, Ji-rong Wen, Wei-ying Ma
In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from...
1 VIPS: a Vision-based Page Segmentation Algorithm (2003)
Deng Cai, Shipeng Yu, Ji-rong Wen, Wei-ying Ma, Deng Cai, Shipeng Yu, ...
A new web content structure analysis based on visual representation is proposed in this paper. Many web applications such as information retrieval, information extraction and automatic page...
Improving pseudo-relevance feedback in web information retrieval using web page segmentation (2003)
Shipeng Yu, Deng Cai, Ji-rong Wen, Wei-ying Ma
In contrast to traditional document retrieval, a web page as a whole is not a good information unit to search because it often contains multiple topics and a lot of irrelevant information from...
Extracting content structure for web pages based on visual representation (2003)
Deng Cai, Shipeng Yu, Ji-rong Wen, Wei-ying Ma
Abstract. A new web content structure based on visual representation is proposed in this paper. Many web applications such as information retrieval, information extraction and automatic page...