Klær, kosmetikk og accessoirer/Herreklær/Luer,skjerf og votter lue,skjerf,votter
Klær, kosmetikk og accessoirer/Herreklær/Undertøy undertøy
Klær, kosmetikk og accessoirer/Herreklær/Smokinger smoking
Klær, kosmetikk og accessoirer/Herreklær/Gensere herregenser
Klær, kosmetikk og accessoirer/Herreklær/Ytterklær ytterklær,ytterjakke
Klær, kosmetikk og accessoirer/Herreklær/Dresser dress
Klær, kosmetikk og accessoirer/Herreklær/Skjorter herreskjorte
Klær, kosmetikk og accessoirer/Herreklær/Bunader herrebunad
Klær, kosmetikk og accessoirer/Sko/Damesko damesko
Klær, kosmetikk og accessoirer/Sko/Herresko herresko
Klær, kosmetikk og accessoirer/Dameklær/T-skjorter t-skjorte
Klær, kosmetikk og accessoirer/Dameklær/Bukser damebukse
Klær, kosmetikk og accessoirer/Dameklær/Jakker damejakke
Klær, kosmetikk og accessoirer/Dameklær/Luer,skjerf og votter lue,skjerf,votter
Klær, kosmetikk og accessoirer/Dameklær/Brudekjoler brudekjole
Klær, kosmetikk og accessoirer/Dameklær/Undertøy dameundertøy
Klær, kosmetikk og accessoirer/Dameklær/Kjoler kjole
Klær, kosmetikk og accessoirer/Dameklær/Topper topper
Klær, kosmetikk og accessoirer/Dameklær/Gensere genser
Klær, kosmetikk og accessoirer/Dameklær/Ytterklær ytterklær,ytterjakke
Klær, kosmetikk og accessoirer/Dameklær/Skjorter bluse
Klær, kosmetikk og accessoirer/Dameklær/Skjørt skjørt
Klær, kosmetikk og accessoirer/Dameklær/Bunader beltestakk
Klær, kosmetikk og accessoirer/Klokker og ur klokke
Klær, kosmetikk og accessoirer/Briller og linser/Solbriller solbriller Klær, kosmetikk og accessoirer/Briller og linser/Briller briller
Klær, kosmetikk og accessoirer/Kosmetikk kosmetikk
Foreldre og barn/Barneklær og sko/Gutt gutteklær
Foreldre og barn/Barneklær og sko/Jente jenteklær
Foreldre og barn/Barneklær og sko/Baby babyklær
Foreldre og barn/Barneseter barnesete
Foreldre og barn/Barnevogner barnevogn
Foreldre og barn/Barnemøbler/Stoler barnestol
Foreldre og barn/Barnemøbler/Stellebord stellebord
Foreldre og barn/Barnemøbler/Senger barneseng
References
Özlem Aslan, Xinhua Zhang, and Dale Schuurmans. Convex deep learning via normalized kernels. InAdvances in Neural Information Processing Systems, pages 3275–3283, 2014.
Aurélien Bellet, Amaury Habrard, and Marc Sebban. A survey on metric learning for feature vectors and structured data.arXiv preprint arXiv:1306.6709, 2013.
David M Blei, Andrew Y Ng, and Michael I Jordan. Latent dirichlet allocation. the Journal of machine Learning research, 3:993–1022, 2003.
Steve Branson, Grant Van Horn, Serge Belongie, and Pietro Perona. Bird species categorization using pose normalized deep convolutional nets.arXiv preprint arXiv:1406.2952, 2014.
Leo Breiman. Random forests.Machine learning, 45(1):5–32, 2001.
Rakesh Chalasani and Jose C Principe. Deep predictive coding networks.arXiv preprint arXiv:1301.3541, 2013.
Tsung-Han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, and Yi Ma.
Pcanet: A simple deep learning baseline for image classification? arXiv preprint arXiv:1404.3606, 2014.
Moses S Charikar. Similarity estimation techniques from rounding algorithms. In Proceedings of the thiry-fourth annual ACM symposium on Theory of computing, pages 380–388. ACM, 2002.
Gal Chechik, Varun Sharma, Uri Shalit, and Samy Bengio. Large scale online learning of image similarity through ranking.The Journal of Machine Learning Research, 11:1109–1135, 2010.
Youngmin Cho and Lawrence K Saul. Kernel methods for deep learning. In Advances in neural information processing systems, pages 342–350, 2009.
Anna Choromanska, Mikael Henaff, Michael Mathieu, Gérard Ben Arous, and Yann LeCun. The loss surface of multilayer networks.arXiv preprint
arXiv:1412.0233, 2014.
George E Dahl, Dong Yu, Li Deng, and Alex Acero. Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition.Audio, Speech, and Language Processing, IEEE Transactions on, 20(1):30–42, 2012.
Navneet Dalal and Bill Triggs. Histograms of oriented gradients for human detection. InComputer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 886–893. IEEE, 2005.
Scott C. Deerwester, Susan T Dumais, Thomas K. Landauer, George W. Furnas, and Richard A. Harshman. Indexing by latent semantic analysis.JAsIs, 41(6):
391–407, 1990.
Kunihiko Fukushima. Cognitron: A self-organizing multilayered neural network.
Biological cybernetics, 20(3-4):121–136, 1975.
Yarin Gal and Zoubin Ghahramani. Dropout as a bayesian approximation: Insights and applications. InDeep Learning Workshop, ICML, 2015.
Xavier Glorot and Yoshua Bengio. Understanding the difficulty of training deep feedforward neural networks. InInternational conference on artificial intelligence and statistics, pages 249–256, 2010.
Ian J Goodfellow and Oriol Vinyals. Qualitatively characterizing neural network optimization problems.arXiv preprint arXiv:1412.6544, 2014.
Kristen Grauman and Rob Fergus. Learning binary hash codes for large-scale image search. InMachine learning for computer vision, pages 49–87. Springer, 2013.
Thomas L Griffiths and Mark Steyvers. Finding scientific topics. Proceedings of the National Academy of Sciences, 101(suppl 1):5228–5235, 2004.
Tom Griffiths. Gibbs sampling in the generative model of latent dirichlet allocation. 2002.
Michael Gutmann and Aapo Hyvärinen. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. InInternational Conference on Artificial Intelligence and Statistics, pages 297–304, 2010.
LI Hang. A short introduction to learning to rank. IEICE TRANSACTIONS on Information and Systems, 94(10):1854–1862, 2011.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.arXiv preprint arXiv:1502.01852, 2015.
Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov. Improving neural networks by preventing co-adaptation of feature detectors.arXiv preprint arXiv:1207.0580, 2012.
Sepp Hochreiter. Untersuchungen zu dynamischen neuronalen netzen. Diploma, Technische Universität München, 1991.
Andrej Karpathy and Li Fei-Fei. Deep visual-semantic alignments for generating image descriptions.arXiv preprint arXiv:1412.2306, 2014.
Douwe Kiela and Léon Bottou. Learning image embeddings using convolutional neural networks for improved multi-modal semantics. InProceedings of EMNLP, volume 2014, 2014.
Ryan Kiros, Ruslan Salakhutdinov, and Richard S Zemel. Unifying visual-semantic embeddings with multimodal neural language models.arXiv preprint
arXiv:1411.2539, 2014.
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. Imagenet classification with deep convolutional neural networks. InAdvances in neural information processing systems, pages 1097–1105, 2012.
Brian Kulis. Metric learning: A survey.Foundations and Trends in Machine Learning, 5(4):287–364, 2012.
Quoc V Le and Tomas Mikolov. Distributed representations of sentences and documents.arXiv preprint arXiv:1405.4053, 2014.
Yann LeCun, Bernhard Boser, John S Denker, Donnie Henderson, Richard E Howard, Wayne Hubbard, and Lawrence D Jackel. Backpropagation applied to handwritten zip code recognition.Neural computation, 1(4):541–551, 1989.
Omer Levy and Yoav Goldberg. Neural word embedding as implicit matrix factorization. InAdvances in Neural Information Processing Systems, pages 2177–2185, 2014.
Omer Levy, Yoav Goldberg, and Ido Dagan. Improving distributional similarity with lessons learned from word embeddings.Transactions of the Association for Computational Linguistics, 3:211–225, 2015.
M. Lin, Q. Chen, and S. Yan. Network in network. arXiv preprint arXiv:1312.4400, 2013.
David G Lowe. Object recognition from local scale-invariant features. InComputer vision, 1999. The proceedings of the seventh IEEE international conference on, volume 2, pages 1150–1157. Ieee, 1999.
Tomasz Malisiewicz. From feature descriptors to deep learning: 20 years of computer vision, 2015. URLhttp://www.computervisionblog.com/
2015/01/from-feature-descriptors-to-deep.html.
Pankaj Mehta and David J Schwab. An exact mapping between the variational renormalization group and deep learning.arXiv preprint arXiv:1410.3831, 2014.
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean.
Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems, pages 3111–3119, 2013.
Thomas Minka. Estimating a dirichlet distribution, 2000.
Thomas Minka and John Lafferty. Expectation-propagation for the generative aspect model. InProceedings of the Eighteenth conference on Uncertainty in artificial intelligence, pages 352–359. Morgan Kaufmann Publishers Inc., 2002.
Guido F Montufar, Razvan Pascanu, Kyunghyun Cho, and Yoshua Bengio. On the number of linear regions of deep neural networks. InAdvances in Neural Information Processing Systems, pages 2924–2932, 2014.
Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg S Corrado, and Jeffrey Dean. Zero-shot learning by convex combination of semantic embeddings.arXiv preprint arXiv:1312.5650, 2013.
Frank Rosenblatt. The perceptron: a probabilistic model for information storage and organization in the brain.Psychological review, 65(6):386, 1958.
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams. Learning representations by back-propagating errors.Cognitive modeling, 5:3, 1988.
Richard Socher, Cliff C Lin, Chris Manning, and Andrew Y Ng. Parsing natural scenes and natural language with recursive neural networks. InProceedings of the 28th international conference on machine learning (ICML-11), pages 129–136, 2011.
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. Dropout: A simple way to prevent neural networks from overfitting.The Journal of Machine Learning Research, 15(1):1929–1958, 2014.
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton. On the importance of initialization and momentum in deep learning. InProceedings of the 30th international conference on machine learning (ICML-13), pages
1139–1147, 2013.