Distance-Preserving Probabilistic Embeddings with Side Information: Variational Bayesian Multidimensional Scaling Gaussian Process
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[1] Neil D. Lawrence,et al. Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models , 2005, J. Mach. Learn. Res..
[2] K. T. Poole,et al. Bayesian Metric Multidimensional Scaling , 2012, Political Analysis.
[3] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[4] Ruslan Salakhutdinov,et al. Probabilistic Matrix Factorization , 2007, NIPS.
[5] K. Whitehouse,et al. A robustness analysis of multi-hop ranging-based localization approximations , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.
[6] David C. Moore,et al. Robust distributed network localization with noisy range measurements , 2004, SenSys '04.
[7] John W. Sammon,et al. A Nonlinear Mapping for Data Structure Analysis , 1969, IEEE Transactions on Computers.
[8] Michael E. Tipping,et al. NeuroScale: Novel Topographic Feature Extraction using RBF Networks , 1996, NIPS.
[9] Jarkko Venna,et al. Local multidimensional scaling , 2006, Neural Networks.
[10] Kj Love,et al. A political analysis , 2003 .
[11] L. Christophorou. Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.
[12] Neil D. Lawrence,et al. Gaussian Processes for Big Data , 2013, UAI.
[13] Patrick J. F. Groenen,et al. Modern Multidimensional Scaling: Theory and Applications , 2003 .
[14] D. Signorini,et al. Neural networks , 1995, The Lancet.
[15] Ying Zhang,et al. Localization from mere connectivity , 2003, MobiHoc '03.
[16] Yee Whye Teh,et al. Variational Bayesian Approach to Movie Rating Prediction , 2007, KDD 2007.
[17] A. M. Mathai,et al. Quadratic forms in random variables : theory and applications , 1992 .
[18] Michael C. Hout,et al. Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.
[19] Quoc V. Le,et al. Exploiting Similarities among Languages for Machine Translation , 2013, ArXiv.
[20] Michalis K. Titsias,et al. Variational Learning of Inducing Variables in Sparse Gaussian Processes , 2009, AISTATS.
[21] Andrew McCallum,et al. Word Representations via Gaussian Embedding , 2014, ICLR.
[22] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[23] Joaquin Quiñonero Candela,et al. Local distance preservation in the GP-LVM through back constraints , 2006, ICML.
[24] Guillermo Sapiro,et al. Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information , 2012, SDM.
[25] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[26] R N Shepard,et al. Multidimensional Scaling, Tree-Fitting, and Clustering , 1980, Science.
[27] Tommi S. Jaakkola,et al. Word, graph and manifold embedding from Markov processes , 2015, ArXiv.
[28] Geoffrey E. Hinton,et al. Stochastic Neighbor Embedding , 2002, NIPS.
[29] W. Torgerson. Multidimensional scaling: I. Theory and method , 1952 .
[30] Neil D. Lawrence,et al. Bayesian Gaussian Process Latent Variable Model , 2010, AISTATS.
[31] Richard Socher,et al. A Neural Network for Factoid Question Answering over Paragraphs , 2014, EMNLP.