Details of Research Outputs

TitleModeling Winner-Take-All Competition in Sparse Binary Projections
Author (Name in English or Pinyin)
Date Issued2021
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN03029743
DOI10.1007/978-3-030-67658-2_26
Indexed BySCOPUS
Published range国外学术期刊
Volume Issue Pages卷: 12457 LNAI 页: 456-472
References
[1] Ailon, N., Chazelle, B.: The fast Johnson-Lindenstrauss transform and approximate nearest neighbors. SIAM J. Comput. 39(1), 302–322 (2009)
[2] Arbib, M.: The Handbook of Brain Theory and Neural Networks. MIT Press, Cambridge (2003)
[3] Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval, vol. 463. ACM Press, Cambridge (1999)
[4] Bingham, E., Mannila, H.: Random projection in dimensionality reduction: applications to image and text data. In: Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 245–250. ACM (2001)
[5] Caron, S., Ruta, V., Abbott, L., Axel, R.: Random convergence of olfactory inputs in the drosophila mushroom body. Nature 497(7447), 113 (2013)
[6] Charikar, M.: Similarity estimation techniques from rounding algorithms. In: Proceedings of the 34th Annual ACM Symposium on Theory of Computing, pp. 380– 388. ACM (2002)
[7] Dasgupta, S., Stevens, C., Navlakha, S.: A neural algorithm for a fundamental computing problem. Science 358(6364), 793–796 (2017)
[8] Frank, M., Wolfe, P.: An algorithm for quadratic programming. Naval Res. Logist. 3(1–2), 95–110 (1956)
[9] Gionis, A., Indyk, P., Motwani, R.: Similarity search in high dimensions via hashing. In: Proceedings of the 25th International Conference on Very Large Data Bases, vol. 99, pp. 518–529 (1999)
[10] Gong, Y., Lazebnik, S., Gordo, A., Perronnin, F.: Iterative quantization: a procrustean approach to learning binary codes for large-scale image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 35(12), 2916–2929 (2012)
[11] Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157–1182 (2003)
[12] Heo, J., Lee, Y., He, J., Chang, S., Yoon, S.: Spherical hashing: Binary code embedding with hyperspheres. IEEE Trans. Pattern Anal. Mach. Intell. 37(11), 2304–2316 (2015)
[13] Jaggi, M.: Revisiting Frank-Wolfe: projection-free sparse convex optimization. In: Proceedings of the 30th International Conference on Machine Learning, pp. 427– 435 (2013)
[14] Jain, A., Murty, N., Flynn, P.: Data clustering: a review. ACM Comput. Surv. 31(3), 264–323 (1999)
[15] Johnson, W., Lindenstrauss, J.: Extensions of Lipschitz mappings into a Hilbert space. Contemporary Mathematics 26(189–206), 1 (1984)
[16] Knuth, D.: The Art of Computer Programming, Sorting and Searching, vol. 3. Addison-Wesley, Reading (1998)
[17] Kohonen, T.: The self-organizing map. Proc. IEEE 78(9), 1464–1480 (1990)
[18] Kong, W., Li, W.: Isotropic hashing. In: Advances in Neural Information Processing Systems, pp. 1646–1654 (2012)
[19] Li, W., Mao, J., Zhang, Y., Cui, S.: Fast similarity search via optimal sparse lifting. In: Advances in Neural Information Processing Systems, pp. 176–184 (2018)
[20] Lynch, N., Musco, C., Parter, M.: Winner-take-all computation in spiking neural networks. arXiv preprint arXiv:1904.12591 (2019)
[21] Maass, W.: On the computational power of winner-take-all. Neural Comput. 12(11), 2519–2535 (2000)
[22] MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, Oakland, CA, USA, vol. 1, pp. 281–297 (1967)
[23] Manning, C., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press, Cambridge (2008)
[24] Olsen, S., Bhandawat, V., Wilson, R.: Divisive normalization in olfactory population codes. Neuron 66(2), 287–299 (2010)
[25] Omondi, A., Rajapakse, J.: FPGA Implementations of Neural Networks, vol. 365. Springer, Heidelberg (2006). https://doi.org/10.1007/0-387-28487-7
[26] Panousis, K., Chatzis, S., Theodoridis, S.: Nonparametric Bayesian deep networks with local competition. In: Proceedings of the 36th International Conference on Machine Learning, pp. 4980–4988 (2019)
[27] Pehlevan, C., Sengupta, A., Chklovskii, D.: Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks? Neural Comput. 30(1), 84–124 (2018)
[28] Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 1532–1543 (2014)
[29] Powell, M.: On search directions for minimization algorithms. Math. Program. 4(1), 193–201 (1973)
[30] Russakovsky, O., Deng, J., Su, H., et al.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vision 115(3), 211–252 (2015)
[31] Stevens, C.: What the fly’s nose tells the fly’s brain. Proc. Natl. Acad. Sci. 112(30), 9460–9465 (2015)
[32] Turner, G., Bazhenov, M., Laurent, G.: Olfactory representations by drosophila mushroom body neurons. J. Neurophysiol. 99(2), 734–746 (2008)
[33] Zheng, Z., Lauritzen, S., Perlman, E., Robinson, C., et al.: A complete electron microscopy volume of the brain of adult drosophila melanogaster. Cell 174(3), 730–743 (2018)
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttps://irepository.cuhk.edu.cn/handle/3EPUXD0A/2009
CollectionSchool of Data Science
Corresponding AuthorLi, W.
Affiliation
1.The Chinese University of Hong Kong, Shenzhen, China
2.Shenzhen Research Institute of Big Data, Shenzhen, China
First Author AffilicationShenzhen Research Institute of Big Data
Corresponding Author AffilicationShenzhen Research Institute of Big Data
Recommended Citation
GB/T 7714
Li, W. Modeling Winner-Take-All Competition in Sparse Binary Projections[J]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2021.
APA Li, W. (2021). Modeling Winner-Take-All Competition in Sparse Binary Projections. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
MLA Li, W.."Modeling Winner-Take-All Competition in Sparse Binary Projections".Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2021).
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