Dengyong Zhou

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Learning with Local and Global Consistency

Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf
NIPS
2003

We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised… (More)

Recommender systems with social regularization

Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, Irwin King
WSDM
2011

Although Recommender Systems have been comprehensively analyzed in the past decade, the study of social-based recommender systems just started. In this paper, aiming at providing a general method for… (More)

Learning with Hypergraphs: Clustering, Classification, and Embedding

Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
NIPS
2006

We usually endow the investigated objects with pairwise relationships, which can be illustrated as graphs. In many real-world problems, however, relationships among the objects of our interest are… (More)

Ranking on Data Manifolds

Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
NIPS
2003

The Google search engine has enjoyed huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a… (More)

Learning from labeled and unlabeled data on a directed graph

Dengyong Zhou, Jiayuan Huang, Bernhard Schölkopf
ICML
2005

We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is considered. The time… (More)

Semi-Supervised Graph-Based Hyperspectral Image Classification

Gustavo Camps-Valls, Tatyana V. Bandos Marsheva, Dengyong Zhou
IEEE Transactions on Geoscience and Remote…
2007

This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed to handle the special characteristics of hyperspectral images, namely,… (More)

Spectral clustering and transductive learning with multiple views

We consider spectral clustering and transductive inference for data with multiple views. A typical example is the web, which can be described by either the hyperlinks between web pages or the words… (More)

Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing

Yuchen Zhang, Xi Chen, Dengyong Zhou, Michael I. Jordan
NIPS
2014

The Dawid-Skene estimator has been widely used for inferring the true labels from the noisy labels provided by non-expert crowdsourcing workers. However, since the estimator maximizes a non-convex… (More)

Evolutionary spectral clustering by incorporating temporal smoothness

Yun Chi, Xiaodan Song, Dengyong Zhou, Koji Hino, Belle L. Tseng
KDD
2007

Evolutionary clustering is an emerging research area essential to important applications such as clustering dynamic Web and blog contents and clustering data streams. In evolutionary clustering, a… (More)

Semi-supervised protein classification using cluster kernels

Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble
Bioinformatics
2003

MOTIVATION Building an accurate protein classification system depends critically upon choosing a good representation of the input sequences of amino acids. Recent work using string kernels for… (More)

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