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This paper presents a novel model for multimodal learning based on gated neural networks.
Adaptive mixtures of local experts
Robert A Jacobs, Michael I Jordan, Steven J Nowlan, and Geoffrey E Hinton · 1991
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Janvin · 2003
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A Film Classifier Based on Low-level Visual Features
Hui-Yu Huang, Weir-Sheng Shih, and Wen-Hsing Hsu · 2007
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Learning to recognize webpage genres
Ioannis Kanaris and Efstathios Stamatatos · 2009
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Multimodal fusion for multimedia analysis: a survey
Pradeep K. Atrey, M. Anwar Hossain, Abdulmotaleb El Saddik, and Mohan S. Kankanhalli · 2010
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Multimedia data mining: state of the art and challenges
Chidansh Bhatt and Mohan Kankanhalli · 2011
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The importance of encoding versus training with sparse coding and vector quantization
Adam Coates and Andrew Y Ng · 2011
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Multimodal Deep Learning
J Ngiam, A Khosla, and M Kim · 2011
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Random search for hyper-parameter optimization
James Bergstra and Yoshua Bengio · 2012
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Improving word representations via global context and multiple word prototypes
Eric H Huang, Richard Socher, Christopher D Manning, and Andrew Ng · 2012
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Deep learning to hash with multiple representations
Yoonseop Kang, Saehoon Kim, and Seungjin Choi · 2012
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An extensive experimental comparison of methods for multi-label learning
Gjorgji Madjarov, Dragi Kocev, Dejan Gjorgjevikj, and Sašo Džeroski · 2012
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Animated movie genre detection using symbolic fusion of text and image descriptors
Gregory Pais, Patrick Lambert, Daniel Beauchene, Francoise Deloule, and Bogdan Ionescu · 2012
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Multimodal Learning with Deep Boltzmann Machines
Nitish Srivastava and Ruslan Salakhutdinov · 2012
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Twenty years of mixture of experts
Seniha Esen Yuksel, Joseph N Wilson, and Paul D Gader · 2012
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Deep canonical correlation analysis
Galen Andrew, Raman Arora, Jeff A Bilmes, and Karen Livescu · 2013
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A tutorial survey of architectures, algorithms, and applications for deep learning
Li Deng · 2013
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Constructing hierarchical image-tags bimodal representations for word tags alternative choice
Fangxiang Feng, Ruifan Li, and Xiaojie Wang · 2013
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DeViSE: A Deep Visual-Semantic Embedding Model
Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, Marc \ \backslash textquotesingle Aurelio Ranzato, and Tomas Mikolov · 2013
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Maxout networks
Ian Goodfellow, David Warde-farley, Mehdi Mirza, Aaron Courville, and Yoshua Bengio · 2013
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Unsupervised multimodal feature learning for semantic image segmentation
Deli Pei, Huaping Liu, Yulong Liu, and Fuchun Sun · 2013
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Movie Classification Using k-Means and Hierarchical Clustering
Explain images with multimodal recurrent neural networks
Junhua Mao, Wei Xu, Yi Yang, Jiang Wang, and Alan L Yuille · 2014
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Zero-Shot Learning by Convex Combination of Semantic Embeddings
Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg S Corrado, and Jeff Dean · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Grounded Compositional Semantics for Finding and Describing Images with Sentences
Richard Socher, Andrej Karpathy, Quoc V Le, Christopher D Manning, and Andrew Y Ng · 2014
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Challenge Huawei challenge: Fusing multimodal features with deep neural networks for Mobile Video Annotation
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Dharak Shah, Saheb Motiani, and Vishrut Patel · 2013
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Zero-Shot Learning Through Cross-Modal Transfer
Richard Socher, Milind Ganjoo, Christopher D Manning, and Andrew Ng · 2013
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Deep learning-based feature representation for AD/MCI classification
Heung Il Suk and Dinggang Shen · 2013
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Online multimodal deep similarity learning with application to image retrieval
Pengcheng Wu, Steven C.H. Hoi, Hao Xia, Peilin Zhao, Dayong Wang, and Chunyan Miao · 2013
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Zero-Shot Learning with Structured Embeddings
Zeynep Akata, Honglak Lee, and Bernt Schiele · 2014
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Evaluating folksonomy information sources for genre prediction
Deepa Anand · 2014
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Movie posters classification into genres based on low-level features
Marina Ivasic-Kos, Miran Pobar, and Luka Mikec · 2014
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Jian Tu, Zuxuan Wu, Qi Dai, Yu-Gang Jiang, and Xiangyang Xue · 2014
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Topic Modeling of Multimodal Data: an Autoregressive Approach
Yin Zheng, YJ Zhang, and Hugo Larochelle · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh · 2015
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Fast Film Genres Classification Combining Poster and Synopsis
Zhikang Fu, Bing Li, Jun Li, and Shuhua Wei · 2015
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Multimodal PLSA for Movie Genre Classification
Hao-Zhi Hong and Jen-Ing G Hwang · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Automatic Movie Posters Classification into Genres
Marina Ivasic-Kos, Miran Pobar, and Ivo Ipsic · 2015
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Densecap: Fully convolutional localization networks for dense captioning
Justin Johnson, Andrej Karpathy, and Li Fei-Fei · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Blocks and fuel: Frameworks for deep learning
Bart Van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, and Yoshua Bengio · 2015
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Show and tell: A neural image caption generator
Oriol Vinyals, Alexander Toshev, Samy Bengio, and Dumitru Erhan · 2015
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard S Zemel, and Yoshua Bengio · 2015
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