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Deep Learning algorithms attempt to discover good representations, at multiple levels of abstraction. Deep Learning is a topic of broad interest, both to researchers who develop new algorithms and theories, as well as to the rapidly growing number of practitioners who apply these algorithms to a wider range of applications, from vision and speech processing, to natural language understanding, neuroscience, health, etc. Major conferences in these fields often dedicate several sessions to this topic, attesting the widespread interest of our community in this area of research.
There has been very rapid and impressive progress in this area in recent years, in terms of both algorithms and applications, but many challenges remain. This symposium aims at bringing together researchers in Deep Learning and related areas to discuss the new advances, the challenges we face, and to brainstorm about new solutions and directions.
Author Information
Yoshua Bengio (Université of Montréal)
Marc'Aurelio Ranzato (Facebook AI Research)
Honglak Lee (U. Michigan)
Max Welling (University of Amsterdam)
Andrew Y Ng (Baidu Research)
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Jiquan Ngiam · Pang Wei Koh · Zhenghao Chen · Sonia A Bhaskar · Andrew Y Ng -
2011 Poster: Statistical Tests for Optimization Efficiency »
Levi Boyles · Anoop Korattikara · Deva Ramanan · Max Welling -
2011 Demonstration: Haptic Belt with Pedestrian Detection »
Jean Feng · Marc Rasi · Andrew Y Ng · Quoc V. Le · Morgan Quigley · Justin K Chen · Tiffany Low · Will Y Zou -
2011 Poster: Selecting Receptive Fields in Deep Networks »
Adam Coates · Andrew Y Ng -
2011 Poster: Unsupervised learning models of primary cortical receptive fields and receptive field plasticity »
Andrew M Saxe · Maneesh Bhand · Ritvik Mudur · Bipin Suresh · Andrew Y Ng -
2010 Workshop: Deep Learning and Unsupervised Feature Learning »
Honglak Lee · Marc'Aurelio Ranzato · Yoshua Bengio · Geoffrey E Hinton · Yann LeCun · Andrew Y Ng -
2010 Poster: On Herding and the Perceptron Cycling Theorem »
Andrew E Gelfand · Yutian Chen · Laurens van der Maaten · Max Welling -
2010 Poster: Generating more realistic images using gated MRF's »
Marc'Aurelio Ranzato · Volodymyr Mnih · Geoffrey E Hinton -
2010 Poster: Tiled convolutional neural networks »
Quoc V. Le · Jiquan Ngiam · Zhenghao Chen · Daniel Jin hao Chia · Pang Wei Koh · Andrew Y Ng -
2010 Poster: Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine »
George Dahl · Marc'Aurelio Ranzato · Abdel-rahman Mohamed · Geoffrey E Hinton -
2010 Poster: Energy Disaggregation via Discriminative Sparse Coding »
J. Zico Kolter · Siddarth Batra · Andrew Y Ng -
2009 Mini Symposium: Machine Learning for Sustainability »
J. Zico Kolter · Thomas Dietterich · Andrew Y Ng -
2009 Poster: Measuring Invariances in Deep Networks »
Ian Goodfellow · Quoc V. Le · Andrew M Saxe · Andrew Y Ng -
2009 Poster: Unsupervised feature learning for audio classification using convolutional deep belief networks »
Honglak Lee · Peter Pham · Yan Largman · Andrew Y Ng -
2008 Session: Oral session 10: Nonparametric Processes, Scene Processing and Image Statistics »
Max Welling -
2008 Poster: Asynchronous Distributed Learning of Topic Models »
Arthur Asuncion · Padhraic Smyth · Max Welling -
2008 Demonstration: High-Accuracy 3D Sensing for Mobile Manipulators »
Stephen Gould · Morgan Quigley · Siddarth Batra · Ellen Klingbiel · Quoc V Le · Andrew Y Ng -
2007 Poster: Sparse deep belief net model for visual area V2 »
Honglak Lee · Ekanadham Chaitanya · Andrew Y Ng -
2007 Demonstration: Holistic Scene Understanding from Visual and Range Data »
Stephen Gould · Morgan Quigley · Andrew Y Ng · Daphne Koller -
2007 Spotlight: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2007 Spotlight: Collapsed Variational Inference for HDP »
Yee Whye Teh · Kenichi Kurihara · Max Welling -
2007 Spotlight: Distributed Inference for Latent Dirichlet Allocation »
David Newman · Arthur Asuncion · Padhraic Smyth · Max Welling -
2007 Poster: Infinite State Bayes-Nets for Structured Domains »
Max Welling · Ian Porteous · Evgeniy Bart -
2007 Poster: Collapsed Variational Inference for HDP »
Yee Whye Teh · Kenichi Kurihara · Max Welling -
2007 Poster: Distributed Inference for Latent Dirichlet Allocation »
David Newman · Arthur Asuncion · Padhraic Smyth · Max Welling -
2007 Poster: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2007 Spotlight: Infinite State Bayes-Nets for Structured Domains »
Max Welling · Ian Porteous · Evgeniy Bart -
2007 Demonstration: Building a 3-D Model From a Single Still Image »
Ashutosh Saxena · min sun · Andrew Y Ng -
2007 Poster: Efficient multiple hyperparameter learning for log-linear models »
Chuong B Do · Chuan-Sheng Foo · Andrew Y Ng -
2007 Poster: Sparse Feature Learning for Deep Belief Networks »
Marc'Aurelio Ranzato · Y-Lan Boureau · Yann LeCun -
2006 Poster: Efficient Learning of Sparse Representations with an Energy-Based Model »
Marc'Aurelio Ranzato · Christopher Poultney · Sumit Chopra · Yann LeCun -
2006 Poster: Structure Learning in Markov Random Fields »
Sridevi Parise · Max Welling -
2006 Demonstration: Peripheral-Foveal Vision for Real-time Object Recognition »
Benjamin Sapp · Stephen Gould · Adrian Kaehler · Gary R Bradski · Andrew Y Ng -
2006 Spotlight: Efficient Learning of Sparse Representations with an Energy-Based Model »
Marc'Aurelio Ranzato · Christopher Poultney · Sumit Chopra · Yann LeCun -
2006 Poster: Robotic Grasping of Novel Objects »
Ashutosh Saxena · Justin Driemeyer · Justin Kearns · Andrew Y Ng -
2006 Poster: Accelerated Variational Dirichlet Process Mixtures »
Kenichi Kurihara · Max Welling · Nikos Vlassis -
2006 Poster: Map-Reduce for Machine Learning on Multicore »
Cheng-Tao Chu · Sang Kyun Kim · Yi-An Lin · YuanYuan Yu · Gary R Bradski · Andrew Y Ng · Kunle Olukotun -
2006 Poster: An Application of Reinforcement Learning to Aerobatic Helicopter Flight »
Pieter Abbeel · Adam P Coates · Andrew Y Ng · Morgan Quigley -
2006 Spotlight: Accelerated Variational Dirichlet Process Mixtures »
Kenichi Kurihara · Max Welling · Nikos Vlassis -
2006 Talk: Map-Reduce for Machine Learning on Multicore »
Cheng-Tao Chu · Sang Kyun Kim · Yi-An Lin · YuanYuan Yu · Gary R Bradski · Andrew Y Ng · Kunle Olukotun -
2006 Spotlight: Robotic Grasping of Novel Objects »
Ashutosh Saxena · Justin Driemeyer · Justin Kearns · Andrew Y Ng -
2006 Talk: An Application of Reinforcement Learning to Aerobatic Helicopter Flight »
Pieter Abbeel · Adam P Coates · Andrew Y Ng · Morgan Quigley -
2006 Poster: A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation »
Yee Whye Teh · David Newman · Max Welling -
2006 Poster: Efficient sparse coding algorithms, end-stopping and nCRF surround suppression »
Honglak Lee · Alexis Battle · Raina Rajat · Andrew Y Ng