Fast Fisher discriminant analysis with randomized algorithms
•We propose to use random projection to accelerate Fisher discriminant analysis and provide a theoretical analysis. Empirical study shows our method is effective and efficient.•We propose to use random feature map to accelerate kernel discriminant analysis. And we provide theoretical and empirical a...
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| Published in: | Pattern recognition Vol. 72; pp. 82 - 92 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.12.2017
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| ISSN: | 0031-3203, 1873-5142 |
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| Abstract | •We propose to use random projection to accelerate Fisher discriminant analysis and provide a theoretical analysis. Empirical study shows our method is effective and efficient.•We propose to use random feature map to accelerate kernel discriminant analysis. And we provide theoretical and empirical analysis to show the effectiveness and efficiency of our methods.
Fisher discriminant analysis is a classical method for classification and dimension reduction jointly. Regularized FDA (RFDA) and kernel FAD (KFDA) are two important variants. However, RFDA will get stuck in computational burden due to either the high dimension of data or the big number of data and KFDA has similar computational burden due to kernel operations. We propose fast FDA algorithms based on random projection and random feature map to accelerate FDA and kernel FDA. We give theoretical guarantee that the fast FDA algorithms using random projection have good generalization ability in comparison with the conventional regularized FDA. We also give a theoretical guarantee that the pseudoinverse FDA based on random feature map can share similar generalization ability with the conventional kernel FDA. Experimental results further validate that our methods are powerful. |
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| AbstractList | •We propose to use random projection to accelerate Fisher discriminant analysis and provide a theoretical analysis. Empirical study shows our method is effective and efficient.•We propose to use random feature map to accelerate kernel discriminant analysis. And we provide theoretical and empirical analysis to show the effectiveness and efficiency of our methods.
Fisher discriminant analysis is a classical method for classification and dimension reduction jointly. Regularized FDA (RFDA) and kernel FAD (KFDA) are two important variants. However, RFDA will get stuck in computational burden due to either the high dimension of data or the big number of data and KFDA has similar computational burden due to kernel operations. We propose fast FDA algorithms based on random projection and random feature map to accelerate FDA and kernel FDA. We give theoretical guarantee that the fast FDA algorithms using random projection have good generalization ability in comparison with the conventional regularized FDA. We also give a theoretical guarantee that the pseudoinverse FDA based on random feature map can share similar generalization ability with the conventional kernel FDA. Experimental results further validate that our methods are powerful. |
| Author | Li, Yujun Ye, Haishan Zhang, Zhihua Chen, Cheng |
| Author_xml | – sequence: 1 givenname: Haishan surname: Ye fullname: Ye, Haishan email: yhs12354123@163.com organization: Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, China – sequence: 2 givenname: Yujun surname: Li fullname: Li, Yujun email: liyujun145@gmail.com organization: Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, China – sequence: 3 givenname: Cheng surname: Chen fullname: Chen, Cheng email: jackchen1990@gmail.com organization: Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai 200240, China – sequence: 4 givenname: Zhihua surname: Zhang fullname: Zhang, Zhihua email: zhzhang@math.pku.edu.cn organization: School of Mathematical Sciences, Peking University, Beijing 100871, China |
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| Cites_doi | 10.1109/34.908974 10.1109/TGRS.2014.2326655 10.1117/12.605553 10.1137/090771806 10.1137/S0895479804442334 10.1109/34.598228 10.1561/0400000060 10.1162/089976600300014980 10.1007/s00778-003-0098-9 10.1198/016214502753479248 10.1142/S1793536911000787 10.1109/TPAMI.2005.110 10.1007/s00211-010-0331-6 |
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| References | Halko, Martinsson, Tropp (bib0014) 2011; 53 Lopez-Paz, Sra, Smola, Ghahramani, Schölkopf (bib0022) 2014; 32 Baudat, Anouar (bib0009) 2000; 12 Bingham, Mannila (bib0017) 2001 Tu, Zhang, Wang, Qian (bib0008) 2014 Drineas, Mahoney, Muthukrishnan, Sarlós (bib0015) 2011; 117 Hamid, Xiao, Gittens, DeCoste (bib0030) 2014 Le, Sarlós, Smola (bib0024) 2013 Tropp (bib0028) 2011; 3 Belhumeur, Hespanha, Kriegman (bib0001) 1997; 19 Martínez, Kak (bib0002) 2001; 23 Drineas, Magdon-Ismail, Mahoney, Woodruff (bib0025) 2012; 13 Chakrabarti, Roy, Soundalgekar (bib0003) 2003; 12 Dudoit, Fridlyand, Speed (bib0005) 2002; 97 Huang, Deng, Hasegawa-Johnson, He (bib0023) 2013 Ye, Li (bib0007) 2005; 27 Rahimi, Recht (bib0021) 2007 Park, Park (bib0011) 2005; 27 Dasgupta, Drineas, Harb, Josifovski, Mahoney (bib0004) 2007 Goal, Bebis, Nefian (bib0018) 2005; 5779 Tropp (bib0032) 2015; 8 Roth, Steinhage (bib0012) 1999; 12 Cohen, Nelson, Woodruff (bib0029) 2016 Nelson, Nguyên (bib0026) 2013 Mahoney (bib0031) 2011; 3 Clarkson, Woodruff (bib0020) 2013 Woodruff (bib0027) 2014; 10 Zhang, Dai, Xu, Jordan (bib0013) 2010; 11 Golub, Van Loan (bib0006) 2012; 3 Yuan, Zhu, Wang (bib0016) 2015; 53 Mika, Rätsch, Weston, Schölkopf, Smola, Müller (bib0010) 1999 Paul, Boutsidis, Magdon-Ismail, Drineas (bib0019) 2014; 8 Cohen (10.1016/j.patcog.2017.06.029_bib0029) 2016 Hamid (10.1016/j.patcog.2017.06.029_bib0030) 2014 Belhumeur (10.1016/j.patcog.2017.06.029_bib0001) 1997; 19 Lopez-Paz (10.1016/j.patcog.2017.06.029_bib0022) 2014; 32 Huang (10.1016/j.patcog.2017.06.029_bib0023) 2013 Ye (10.1016/j.patcog.2017.06.029_bib0007) 2005; 27 Park (10.1016/j.patcog.2017.06.029_bib0011) 2005; 27 Woodruff (10.1016/j.patcog.2017.06.029_bib0027) 2014; 10 Baudat (10.1016/j.patcog.2017.06.029_bib0009) 2000; 12 Goal (10.1016/j.patcog.2017.06.029_bib0018) 2005; 5779 Golub (10.1016/j.patcog.2017.06.029_bib0006) 2012; 3 Drineas (10.1016/j.patcog.2017.06.029_bib0015) 2011; 117 Mika (10.1016/j.patcog.2017.06.029_bib0010) 1999 Rahimi (10.1016/j.patcog.2017.06.029_bib0021) 2007 Clarkson (10.1016/j.patcog.2017.06.029_bib0020) 2013 Martínez (10.1016/j.patcog.2017.06.029_bib0002) 2001; 23 Le (10.1016/j.patcog.2017.06.029_bib0024) 2013 Nelson (10.1016/j.patcog.2017.06.029_bib0026) 2013 Dasgupta (10.1016/j.patcog.2017.06.029_bib0004) 2007 Paul (10.1016/j.patcog.2017.06.029_bib0019) 2014; 8 Mahoney (10.1016/j.patcog.2017.06.029_bib0031) 2011; 3 Chakrabarti (10.1016/j.patcog.2017.06.029_bib0003) 2003; 12 Bingham (10.1016/j.patcog.2017.06.029_bib0017) 2001 Roth (10.1016/j.patcog.2017.06.029_bib0012) 1999; 12 Yuan (10.1016/j.patcog.2017.06.029_bib0016) 2015; 53 Halko (10.1016/j.patcog.2017.06.029_bib0014) 2011; 53 Drineas (10.1016/j.patcog.2017.06.029_bib0025) 2012; 13 Dudoit (10.1016/j.patcog.2017.06.029_bib0005) 2002; 97 Tu (10.1016/j.patcog.2017.06.029_bib0008) 2014 Tropp (10.1016/j.patcog.2017.06.029_bib0028) 2011; 3 Tropp (10.1016/j.patcog.2017.06.029_bib0032) 2015; 8 Zhang (10.1016/j.patcog.2017.06.029_bib0013) 2010; 11 |
| References_xml | – start-page: 964 year: 2014 end-page: 972 ident: bib0008 article-title: Making Fisher discriminant analysis scalable publication-title: Proceedings of the Thirty-First International Conference on Machine Learning (ICML-14) – start-page: 1177 year: 2007 end-page: 1184 ident: bib0021 article-title: Random features for large-scale kernel machines publication-title: Proceedings of the Advances in Neural Information Processing Systems – volume: 27 start-page: 929 year: 2005 end-page: 941 ident: bib0007 article-title: A two-stage linear discriminant analysis via QR-decomposition publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 3 start-page: 115 year: 2011 end-page: 126 ident: bib0028 article-title: Improved analysis of the subsampled randomized hadamard transform publication-title: Adv. Adapt. Data Anal. – volume: 23 start-page: 228 year: 2001 end-page: 233 ident: bib0002 article-title: PCA versus LDA publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 11 start-page: 2199 year: 2010 end-page: 2228 ident: bib0013 article-title: Regularized discriminant analysis, ridge regression and beyond publication-title: J. Mach. Learn. Res. – volume: 13 start-page: 3475 year: 2012 end-page: 3506 ident: bib0025 article-title: Fast approximation of matrix coherence and statistical leverage publication-title: J. Mach. Learn. Res. – volume: 10 start-page: 1 year: 2014 end-page: 157 ident: bib0027 article-title: Sketching as a tool for numerical linear algebra publication-title: Found. Trends® Theor. Comput. Sci. – volume: 12 start-page: 2385 year: 2000 end-page: 2404 ident: bib0009 article-title: Generalized discriminant analysis using a kernel approach publication-title: Neural Comput. – volume: 5779 start-page: 426 year: 2005 end-page: 437 ident: bib0018 article-title: Face recognition experiments with random projection publication-title: Proceedings of SPIE – volume: 8 start-page: 22 year: 2014 ident: bib0019 article-title: Random projections for linear support vector machines publication-title: ACM Trans. Knowl. Discov. Data (TKDD) – volume: 12 start-page: 170 year: 2003 end-page: 185 ident: bib0003 article-title: Fast and accurate text classification via multiple linear discriminant projections publication-title: VLDB J. – start-page: 81 year: 2013 end-page: 90 ident: bib0020 article-title: Low rank approximation and regression in input sparsity time publication-title: Proceedings of the Forty-Fifth Annual ACM Symposium on Theory of Computing – volume: 3 start-page: 123 year: 2011 end-page: 224 ident: bib0031 article-title: Randomized algorithms for matrices and data publication-title: Found. Trends® Mach. Learn. – volume: 8 start-page: 1 year: 2015 end-page: 230 ident: bib0032 article-title: An introduction to matrix concentration inequalities publication-title: Found. Trends® Mach. Learn. – volume: 53 start-page: 217 year: 2011 end-page: 288 ident: bib0014 article-title: Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions publication-title: SIAM Rev. – volume: 12 start-page: 568 year: 1999 end-page: 574 ident: bib0012 article-title: Nonlinear discriminant analysis using kernel functions publication-title: Proceedings of the International Conference on Neural Information Processing Systems – volume: 3 year: 2012 ident: bib0006 article-title: Matrix Computations – volume: 117 start-page: 219 year: 2011 end-page: 249 ident: bib0015 article-title: Faster least squares approximation publication-title: Numer. Math. – start-page: 230 year: 2007 end-page: 239 ident: bib0004 article-title: Feature selection methods for text classification publication-title: Proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining – volume: 27 start-page: 87 year: 2005 end-page: 102 ident: bib0011 article-title: Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition publication-title: SIAM J. Matrix Anal. Appl. – volume: 53 start-page: 631 year: 2015 end-page: 644 ident: bib0016 article-title: Hyperspectral band selection by multitask sparsity pursuit publication-title: IEEE Trans. Geosci. Remote Sens. – volume: 32 start-page: II year: 2014 end-page: 1359–II–1367 ident: bib0022 article-title: Randomized nonlinear component analysis publication-title: Proceedings of the Thirty-First International Conference on International Conference on Machine Learning – volume: 97 start-page: 77 year: 2002 end-page: 87 ident: bib0005 article-title: Comparison of discrimination methods for the classification of tumors using gene expression data publication-title: J. Am. Stat. Assoc. – volume: 19 start-page: 711 year: 1997 end-page: 720 ident: bib0001 article-title: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – start-page: 245 year: 2001 end-page: 250 ident: bib0017 article-title: Random projection in dimensionality reduction: applications to image and text data publication-title: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining – start-page: 11:1 year: 2016 end-page: 11:14 ident: bib0029 article-title: Optimal approximate matrix product in terms of stable rank publication-title: Proceedings of the Forty-Third International Colloquium on Automata, Languages, and Programming, ICALP 2016, Rome, Italy – start-page: 117 year: 2013 end-page: 126 ident: bib0026 article-title: OSNAP: Faster numerical linear algebra algorithms via sparser subspace embeddings publication-title: Proceedings of the IEEE Fifty-Fourth Annual Symposium on Foundations of Computer Science (FOCS) – start-page: 526 year: 1999 end-page: 532 ident: bib0010 article-title: Invariant feature extraction and classification in kernel spaces. publication-title: Proceedings of the International Conference on Neural Information Processing Systems – start-page: 244 year: 2013 end-page: 252 ident: bib0024 article-title: Fastfood-computing hilbert space expansions in loglinear time publication-title: Proceedings of the Thirtieth International Conference on Machine Learning (ICML-13) – start-page: 3143 year: 2013 end-page: 3147 ident: bib0023 article-title: Random features for kernel deep convex network publication-title: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) – start-page: 19 year: 2014 end-page: 27 ident: bib0030 article-title: Compact random feature maps. publication-title: Proceedings of the International Conference on Machine Learning – volume: 23 start-page: 228 issue: 2 year: 2001 ident: 10.1016/j.patcog.2017.06.029_bib0002 article-title: PCA versus LDA publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.908974 – volume: 32 start-page: II year: 2014 ident: 10.1016/j.patcog.2017.06.029_bib0022 article-title: Randomized nonlinear component analysis – volume: 11 start-page: 2199 year: 2010 ident: 10.1016/j.patcog.2017.06.029_bib0013 article-title: Regularized discriminant analysis, ridge regression and beyond publication-title: J. Mach. Learn. Res. – volume: 53 start-page: 631 issue: 2 year: 2015 ident: 10.1016/j.patcog.2017.06.029_bib0016 article-title: Hyperspectral band selection by multitask sparsity pursuit publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2326655 – start-page: 11:1 year: 2016 ident: 10.1016/j.patcog.2017.06.029_bib0029 article-title: Optimal approximate matrix product in terms of stable rank – start-page: 244 year: 2013 ident: 10.1016/j.patcog.2017.06.029_bib0024 article-title: Fastfood-computing hilbert space expansions in loglinear time – volume: 13 start-page: 3475 issue: 1 year: 2012 ident: 10.1016/j.patcog.2017.06.029_bib0025 article-title: Fast approximation of matrix coherence and statistical leverage publication-title: J. Mach. Learn. Res. – volume: 5779 start-page: 426 year: 2005 ident: 10.1016/j.patcog.2017.06.029_bib0018 article-title: Face recognition experiments with random projection doi: 10.1117/12.605553 – volume: 53 start-page: 217 issue: 2 year: 2011 ident: 10.1016/j.patcog.2017.06.029_bib0014 article-title: Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions publication-title: SIAM Rev. doi: 10.1137/090771806 – start-page: 3143 year: 2013 ident: 10.1016/j.patcog.2017.06.029_bib0023 article-title: Random features for kernel deep convex network – volume: 27 start-page: 87 issue: 1 year: 2005 ident: 10.1016/j.patcog.2017.06.029_bib0011 article-title: Nonlinear discriminant analysis using kernel functions and the generalized singular value decomposition publication-title: SIAM J. Matrix Anal. Appl. doi: 10.1137/S0895479804442334 – volume: 19 start-page: 711 issue: 7 year: 1997 ident: 10.1016/j.patcog.2017.06.029_bib0001 article-title: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.598228 – start-page: 117 year: 2013 ident: 10.1016/j.patcog.2017.06.029_bib0026 article-title: OSNAP: Faster numerical linear algebra algorithms via sparser subspace embeddings – start-page: 19 year: 2014 ident: 10.1016/j.patcog.2017.06.029_bib0030 article-title: Compact random feature maps. – start-page: 1177 year: 2007 ident: 10.1016/j.patcog.2017.06.029_bib0021 article-title: Random features for large-scale kernel machines – volume: 3 start-page: 123 issue: 2 year: 2011 ident: 10.1016/j.patcog.2017.06.029_bib0031 article-title: Randomized algorithms for matrices and data publication-title: Found. Trends® Mach. Learn. – volume: 10 start-page: 1 issue: 1–2 year: 2014 ident: 10.1016/j.patcog.2017.06.029_bib0027 article-title: Sketching as a tool for numerical linear algebra publication-title: Found. Trends® Theor. Comput. Sci. doi: 10.1561/0400000060 – start-page: 964 year: 2014 ident: 10.1016/j.patcog.2017.06.029_bib0008 article-title: Making Fisher discriminant analysis scalable – start-page: 526 year: 1999 ident: 10.1016/j.patcog.2017.06.029_bib0010 article-title: Invariant feature extraction and classification in kernel spaces. – volume: 12 start-page: 2385 issue: 10 year: 2000 ident: 10.1016/j.patcog.2017.06.029_bib0009 article-title: Generalized discriminant analysis using a kernel approach publication-title: Neural Comput. doi: 10.1162/089976600300014980 – volume: 12 start-page: 170 issue: 2 year: 2003 ident: 10.1016/j.patcog.2017.06.029_bib0003 article-title: Fast and accurate text classification via multiple linear discriminant projections publication-title: VLDB J. doi: 10.1007/s00778-003-0098-9 – volume: 8 start-page: 1 issue: 1–2 year: 2015 ident: 10.1016/j.patcog.2017.06.029_bib0032 article-title: An introduction to matrix concentration inequalities publication-title: Found. Trends® Mach. Learn. – start-page: 81 year: 2013 ident: 10.1016/j.patcog.2017.06.029_bib0020 article-title: Low rank approximation and regression in input sparsity time – volume: 97 start-page: 77 issue: 457 year: 2002 ident: 10.1016/j.patcog.2017.06.029_bib0005 article-title: Comparison of discrimination methods for the classification of tumors using gene expression data publication-title: J. Am. Stat. Assoc. doi: 10.1198/016214502753479248 – volume: 8 start-page: 22 issue: 4 year: 2014 ident: 10.1016/j.patcog.2017.06.029_bib0019 article-title: Random projections for linear support vector machines publication-title: ACM Trans. Knowl. Discov. Data (TKDD) – volume: 12 start-page: 568 year: 1999 ident: 10.1016/j.patcog.2017.06.029_bib0012 article-title: Nonlinear discriminant analysis using kernel functions – volume: 3 year: 2012 ident: 10.1016/j.patcog.2017.06.029_bib0006 – volume: 3 start-page: 115 issue: 01n02 year: 2011 ident: 10.1016/j.patcog.2017.06.029_bib0028 article-title: Improved analysis of the subsampled randomized hadamard transform publication-title: Adv. Adapt. Data Anal. doi: 10.1142/S1793536911000787 – start-page: 230 year: 2007 ident: 10.1016/j.patcog.2017.06.029_bib0004 article-title: Feature selection methods for text classification – volume: 27 start-page: 929 issue: 6 year: 2005 ident: 10.1016/j.patcog.2017.06.029_bib0007 article-title: A two-stage linear discriminant analysis via QR-decomposition publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2005.110 – volume: 117 start-page: 219 issue: 2 year: 2011 ident: 10.1016/j.patcog.2017.06.029_bib0015 article-title: Faster least squares approximation publication-title: Numer. Math. doi: 10.1007/s00211-010-0331-6 – start-page: 245 year: 2001 ident: 10.1016/j.patcog.2017.06.029_bib0017 article-title: Random projection in dimensionality reduction: applications to image and text data |
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| SubjectTerms | Fisher discriminant analysis Random feature map Random projection |
| Title | Fast Fisher discriminant analysis with randomized algorithms |
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