{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T23:04:02Z","timestamp":1793315042797,"version":"4.5.0"},"publisher-location":"New York, NY, USA","reference-count":25,"publisher":"ACM","license":[{"start":{"date-parts":[[2009,6,14]],"date-time":"2009-06-14T00:00:00Z","timestamp":1244937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000185","name":"Defense Advanced Research Projects Agency","doi-asserted-by":"publisher","award":["FA8750-05-2-0249"],"award-info":[{"award-number":["FA8750-05-2-0249"]}],"id":[{"id":"10.13039\/100000185","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2009,6,14]]},"DOI":"10.1145\/1553374.1553453","type":"proceedings-article","created":{"date-parts":[[2009,6,16]],"date-time":"2009-06-16T09:34:36Z","timestamp":1245144876000},"page":"609-616","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1442,"title":["Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations"],"prefix":"10.1145","author":[{"given":"Honglak","family":"Lee","sequence":"first","affiliation":[{"name":"Stanford University, Stanford, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roger","family":"Grosse","sequence":"additional","affiliation":[{"name":"Stanford University, Stanford, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajesh","family":"Ranganath","sequence":"additional","affiliation":[{"name":"Stanford University, Stanford, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew Y.","family":"Ng","sequence":"additional","affiliation":[{"name":"Stanford University, Stanford, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2009,6,14]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0042-6989(97)00121-1"},{"key":"e_1_3_2_1_2_1","volume-title":"Neural Information Processing Systems.","author":"Bengio Y.","year":"2006","unstructured":"Bengio, Y., Lamblin, P., Popovici, D., &amp; Larochelle, H. (2006). Greedy layer-wise training of deep networks. Adv. in Neural Information Processing Systems."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.320"},{"key":"e_1_3_2_1_4_1","volume-title":"echnical Report).","author":"Desjardins G.","year":"2008","unstructured":"Desjardins, G., &amp; Bengio, Y. (2008). Empirical evaluation of convolutional RBMs for vision (Technical Report)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/1032643.1033069"},{"key":"e_1_3_2_1_6_1","volume-title":"Proceedings of the Conference on Uncertainty in AI.","author":"Grosse R.","year":"2007","unstructured":"Grosse, R., Raina, R., Kwong, H., &amp; Ng, A. (2007). Shift-invariant sparse coding for audio classification. Proceedings of the Conference on Uncertainty in AI."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1162\/089976602760128018"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1127647"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.4364-03.2004"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.68"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"e_1_3_2_1_13_1","volume-title":"Sparse deep belief network model for visual area V2. Advances in Neural Information Processing Systems","author":"Lee H.","year":"2008","unstructured":"Lee, H., Ekanadham, C., &amp; Ng, A. Y. (2008). Sparse deep belief network model for visual area V2. Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.20.001434"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.200"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1038\/381607a0"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273592"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553486"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.383157"},{"key":"e_1_3_2_1_20_1","volume-title":"Efficient learning of sparse representations with an energy-based model. Advances in Neural Information Processing Systems (pp. 1137--1144)","author":"Ranzato M.","year":"2006","unstructured":"Ranzato, M., Poultney, C., Chopra, S., &amp; LeCun, Y. (2006). Efficient learning of sparse representations with an energy-based model. Advances in Neural Information Processing Systems (pp. 1137--1144)."},{"key":"e_1_3_2_1_21_1","volume-title":"Neural Information Processing Systems.","author":"Taylor G.","year":"2007","unstructured":"Taylor, G., Hinton, G. E., &amp; Roweis, S. (2007). Modeling human motion using binary latent variables. Adv. in Neural Information Processing Systems."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2007.4408875"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390303"},{"key":"e_1_3_2_1_24_1","volume-title":"Deep learning with kernel regularization for visual recognition. Adv. Neural Information Processing Systems","author":"Yu K.","year":"2009","unstructured":"Yu, K., Xu, W., &amp; Gong, Y. (2009). Deep learning with kernel regularization for visual recognition. Adv. Neural Information Processing Systems."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.301"}],"event":{"name":"ICML '09: The 26th Annual International Conference on Machine Learning held in conjunction with the 2007 International Conference on Inductive Logic Programming","location":"Montreal Quebec Canada","acronym":"ICML '09","sponsor":["MITACS","Microsoft Research Microsoft Research","NSF"]},"container-title":["Proceedings of the 26th Annual International Conference on Machine Learning"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1553374.1553453","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1553374.1553453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,17]],"date-time":"2026-05-17T19:55:32Z","timestamp":1779047732000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1553374.1553453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,6,14]]},"references-count":25,"alternative-id":["10.1145\/1553374.1553453","10.1145\/1553374"],"URL":"https:\/\/doi.org\/10.1145\/1553374.1553453","relation":{},"subject":[],"published":{"date-parts":[[2009,6,14]]},"assertion":[{"value":"2009-06-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}