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2015-01-12T06:47:53Z

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2015-01-12T06:34:30Z

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2015-01-12T06:27:48Z

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2015-01-12T06:23:03Z

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		+	Deep Learning and Representation Learning Workshop: NIPS 2014
		+	Accepted papers
		+	Oral presentations:
		+
		+	cuDNN: Efficient Primitives for Deep Learning (#49)
		+	Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer
		+
		+	Distilling the Knowledge in a Neural Network (#65)
		+	Geoffrey Hinton, Oriol Vinyals, Jeff Dean
		+
		+	Supervised Learning in Dynamic Bayesian Networks (#54)
		+	Shamim Nemati, Ryan Adams
		+
		+	Deeply-Supervised Nets (#2)
		+	Chen-Yu Lee, Saining Xie, Patrick Gallagher, Zhengyou Zhang, Zhuowen Tu
		+
		+
		+
		+	Posters, morning session (11:30-14:45):
		+
		+	Unsupervised Feature Learning from Temporal Data (#3)
		+	Ross Goroshin, Joan Bruna, Arthur Szlam, Jonathan Tompson, David Eigen, Yann LeCun
		+
		+	Autoencoder Trees (#5)
		+	Ozan Irsoy, Ethem Alpaydin
		+
		+	Scheduled denoising autoencoders (#6)
		+	Krzysztof Geras, Charles Sutton
		+
		+	Learning to Deblur (#8)
		+	Christian Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf
		+
		+	A Winner-Take-All Method for Training Sparse Convolutional Autoencoders (#10)
		+	Alireza Makhzani, Brendan Frey
		+
		+	"Mental Rotation" by Optimizing Transforming Distance (#11)
		+	Weiguang Ding, Graham Taylor
		+
		+	On Importance of Base Model Covariance for Annealing Gaussian RBMs (#12)
		+	Taichi Kiwaki, Kazuyuki Aihara
		+
		+	Ultrasound Standard Plane Localization via Spatio-Temporal Feature Learning with Knowledge Transfer (#14)
		+	Hao Chen, Dong Ni, Ling Wu, Sheng Li, Pheng Heng
		+
		+	Understanding Locally Competitive Networks (#15)
		+	Rupesh Srivastava, Jonathan Masci, Faustino Gomez, Jurgen Schmidhuber
		+
		+	Unsupervised pre-training speeds up the search for good features: an analysis of a simplified model of neural network learning (#18)
		+	Avraham Ruderman
		+
		+	Analyzing Feature Extraction by Contrastive Divergence Learning in RBMs (#19)
		+	Ryo Karakida, Masato Okada, Shun-ichi Amari
		+
		+	Deep Tempering (#20)
		+	Guillaume Desjardins, Heng Luo, Aaron Courville, Yoshua Bengio
		+
		+	Learning Word Representations with Hierarchical Sparse Coding (#21)
		+	Dani Yogatama, Manaal Faruqui, Chris Dyer, Noah Smith
		+
		+	Deep Learning as an Opportunity in Virtual Screening (#23)
		+	Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Marvin Steijaert, Jörg Wenger, Hugo Ceulemans, Sepp Hochreiter
		+
		+	Revisit Long Short-Term Memory: An Optimization Perspective (#24)
		+	Qi Lyu, J Zhu
		+
		+	Locally Scale-Invariant Convolutional Neural Networks (#26)
		+	Angjoo Kanazawa, David Jacobs, Abhishek Sharma
		+
		+	Deep Exponential Families (#28)
		+	Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David Blei
		+
		+	Techniques for Learning Binary Stochastic Feedforward Neural Networks (#29)
		+	Tapani Raiko, mathias Berglund, Guillaume Alain, Laurent Dinh
		+
		+	Inside-Outside Semantics: A Framework for Neural Models of Semantic Composition (#30)
		+	Phong Le, Willem Zuidema
		+
		+	Deep Multi-Instance Transfer Learning (#32)
		+	Dimitrios Kotzias, Misha Denil, Phil Blunsom, Nando De Freitas
		+
		+	Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models (#33)
		+	Ryan Kiros, Ruslan Salakhutdinov, Richard Zemel
		+
		+	Retrofitting Word Vectors to Semantic Lexicons (#34)
		+	Manaal Faruqui, Jesse Dodge, Sujay Jauhar, Chris Dyer, Eduard Hovy, Noah Smith
		+
		+	Deep Sequential Neural Network (#35)
		+	Ludovic Denoyer, Patrick Gallinari
		+
		+	Efficient Training Strategies for Deep Neural Network Language Models (#71)
		+	Holger Schwenk
		+
		+
		+
		+
		+	Posters, afternoon session (17:00-18:30):
		+
		+	Deep Learning for Answer Sentence Selection (#36)
		+	Lei Yu, Karl Moritz Hermann, Phil Blunsom, Stephen Pulman
		+
		+	Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition (#37)
		+	Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman
		+
		+	Learning Torque-Driven Manipulation Primitives with a Multilayer Neural Network (#39)
		+	Sergey Levine, Pieter Abbeel
		+
		+	SimNets: A Generalization of Convolutional Networks (#41)
		+	Nadav Cohen, Amnon Shashua
		+
		+	Phonetics embedding learning with side information (#44)
		+	Gabriel Synnaeve, Thomas Schatz, Emmanuel Dupoux
		+
		+	End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results (#45)
		+	Jan Chorowski, Dzmitry Bahdanau, KyungHyun Cho, Yoshua Bengio
		+
		+	BILBOWA: Fast Bilingual Distributed Representations without Word Alignments (#46)
		+	Stephan Gouws, Yoshua Bengio, Greg Corrado
		+
		+	Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling (#47)
		+	Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, Yoshua Bengio
		+
		+	Reweighted Wake-Sleep (#48)
		+	Jorg Bornschein, Yoshua Bengio
		+
		+	Explain Images with Multimodal Recurrent Neural Networks (#51)
		+	Junhua Mao, Wei Xu, Yi Yang, Jiang Wang, Alan Yuille
		+
		+	Rectified Factor Networks and Dropout (#53)
		+	Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter
		+
		+	Towards Deep Neural Network Architectures Robust to Adversarials (#55)
		+	Shixiang Gu, Luca Rigazio
		+
		+	Making Dropout Invariant to Transformations of Activation Functions and Inputs (#56)
		+	Jimmy Ba, Hui Yuan Xiong, Brendan Frey
		+
		+	Aspect Specific Sentiment Analysis using Hierarchical Deep Learning (#58)
		+	Himabindu Lakkaraju, Richard Socher, Chris Manning
		+
		+	Deep Directed Generative Autoencoders (#59)
		+	Sherjil Ozair, Yoshua Bengio
		+
		+	Conditional Generative Adversarial Nets (#60)
		+	Mehdi Mirza, Simon Osindero
		+
		+	Analyzing the Dynamics of Gated Auto-encoders (#61)
		+	Daniel Im, Graham Taylor
		+
		+	Representation as a Service (#63)
		+	Ouais Alsharif, Joelle Pineau, philip bachman
		+
		+	Provable Methods for Training Neural Networks with Sparse Connectivity (#66)
		+	Hanie Sedghi, Anima Anandkumar
		+
		+	Trust Region Policy Optimization (#67)
		+	John D. Schulman, Philipp C. Moritz, Sergey Levine, Michael I. Jordan, Pieter Abbeel
		+
		+	Document Embedding with Paragraph Vectors (#68)
		+	Andrew Dai, Christopher Olah, Quoc Le, Greg Corrado
		+
		+	Backprop-Free Auto-Encoders (#69)
		+	Dong-Hyun Lee, Yoshua Bengio
		+
		+	Rate-Distortion Auto-Encoders (#73)
		+	Luis Sanchez Giraldo, Jose Principe
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Text-2015-01-14 - 版本历史

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