Neural Information Processing
暂无分享,去创建一个
Akira Hirose | Minho Lee | Derong Liu | Kazushi Ikeda | Kenji Doya | Seiichi Ozawa | K. Doya | Minho Lee | S. Ozawa | A. Hirose | Derong Liu | K. Ikeda
[1] C. Quesenberry,et al. A nonparametric estimate of a multivariate density function , 1965 .
[2] B. Liu,et al. Error analysis of digital filters realized with floating-point arithmetic , 1969 .
[3] J. Yackel,et al. Consistency Properties of Nearest Neighbor Density Function Estimators , 1977 .
[4] M. Rosenblatt,et al. Multivariate k-nearest neighbor density estimates , 1979 .
[5] M. Rudemo. Empirical Choice of Histograms and Kernel Density Estimators , 1982 .
[6] L. Györfi,et al. Density-free convergence properties of various estimators of entropy , 1987 .
[7] H. Joe. Estimation of entropy and other functionals of a multivariate density , 1989 .
[8] Kurt Hornik,et al. Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.
[9] L. Györfi,et al. Nonparametric entropy estimation. An overview , 1997 .
[10] James T. Kwok,et al. Objective functions for training new hidden units in constructive neural networks , 1997, IEEE Trans. Neural Networks.
[11] Masashi Sugiyama,et al. Optimal design of regularization term and regularization parameter by subspace information criterion , 2002, Neural Networks.
[12] Liam Paninski,et al. Estimation of Entropy and Mutual Information , 2003, Neural Computation.
[13] Ignacio Rojas,et al. Obtaining Fault Tolerant Multilayer Perceptrons Using an Explicit Regularization , 2000, Neural Processing Letters.
[14] M. N. Goria,et al. A new class of random vector entropy estimators and its applications in testing statistical hypotheses , 2005 .
[15] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[16] Chee Kheong Siew,et al. Universal Approximation using Incremental Constructive Feedforward Networks with Random Hidden Nodes , 2006, IEEE Transactions on Neural Networks.
[17] A. Asuncion,et al. UCI Machine Learning Repository, University of California, Irvine, School of Information and Computer Sciences , 2007 .
[18] Guang-Bin Huang,et al. Convex Incremental Extreme Learning Machine , 2007 .
[19] S. Saigal,et al. Relative performance of mutual information estimation methods for quantifying the dependence among short and noisy data. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[20] Nicolas Pinto,et al. How far can you get with a modern face recognition test set using only simple features? , 2009, CVPR.
[21] Baoxin Li,et al. Discriminative K-SVD for dictionary learning in face recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[22] Andrew Chi-Sing Leung,et al. On the Selection of Weight Decay Parameter for Faulty Networks , 2010, IEEE Transactions on Neural Networks.
[23] Jeffrey Pennington,et al. Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection , 2011, NIPS.
[24] Andrew Chi-Sing Leung,et al. RBF Networks Under the Concurrent Fault Situation , 2012, IEEE Transactions on Neural Networks and Learning Systems.
[25] Zia Ul-Qayyum,et al. Paraphrase Identification using Semantic Heuristic Features , 2012 .
[26] Gang Hua,et al. Probabilistic Elastic Matching for Pose Variant Face Verification , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[27] Josef Kittler,et al. Efficient processing of MRFs for unconstrained-pose face recognition , 2013, 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS).
[28] Andrew Zisserman,et al. Fisher Vector Faces in the Wild , 2013, BMVC.
[29] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[30] Josef Kittler,et al. Class-Specific Kernel Fusion of Multiple Descriptors for Face Verification Using Multiscale Binarised Statistical Image Features , 2014, IEEE Transactions on Information Forensics and Security.
[31] Dimitri Kartsaklis,et al. Evaluating Neural Word Representations in Tensor-Based Compositional Settings , 2014, EMNLP.
[32] Jun Zhao,et al. Relation Classification via Convolutional Deep Neural Network , 2014, COLING.
[33] Christopher Meek,et al. Semantic Parsing for Single-Relation Question Answering , 2014, ACL.
[34] David Zhang,et al. Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification , 2014, International Journal of Computer Vision.
[35] Cícero Nogueira dos Santos,et al. Learning Character-level Representations for Part-of-Speech Tagging , 2014, ICML.
[36] Marios Savvides,et al. Spartans: Single-Sample Periocular-Based Alignment-Robust Recognition Technique Applied to Non-Frontal Scenarios , 2015, IEEE Transactions on Image Processing.
[37] Gang Hua,et al. Hierarchical-PEP model for real-world face recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[38] Kensuke Koshijima,et al. Non-parametric entropy estimators based on simple linear regression , 2015, Comput. Stat. Data Anal..
[39] Alexander M. Rush,et al. Character-Aware Neural Language Models , 2015, AAAI.