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We describe an approach for unsupervised learning of a generic, distributed sentence encoder. Using the continuity of text from books, we train an encoder-decoder model that tries to reconstruct the surrounding sentences of an encoded passage. Sentences that share semantic and syntactic properties are thus mapped to similar vector representations. We next introduce a simple vocabulary expansion method to encode words that were not seen as part of training, allowing us to expand our vocabulary to a million words. After training our model, we extract and evaluate our vectors with linear models on 8 tasks: semantic relatedness, paraphrase detection, image-sentence ranking, question-type classification and 4 benchmark sentiment and subjectivity datasets. The end result is an off-the-shelf encoder that can produce highly generic sentence representations that are robust and perform well in practice. We will make our encoder publicly available.
Author Information
Jamie Kiros (University of Toronto)
Yukun Zhu (University of Toronto)
Russ Salakhutdinov (University of Toronto)
Richard Zemel (University of Toronto)
Raquel Urtasun (University of Toronto)
Antonio Torralba (MIT)
Sanja Fidler (University of Toronto)
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2013 Poster: Learning Stochastic Feedforward Neural Networks »
Yichuan Charlie Tang · Russ Salakhutdinov -
2013 Poster: A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data »
Jasper Snoek · Richard Zemel · Ryan Adams -
2013 Poster: Discriminative Transfer Learning with Tree-based Priors »
Nitish Srivastava · Russ Salakhutdinov -
2013 Poster: Annealing between distributions by averaging moments »
Roger Grosse · Chris Maddison · Russ Salakhutdinov -
2013 Poster: On the Expressive Power of Restricted Boltzmann Machines »
James Martens · Arkadev Chattopadhya · Toni Pitassi · Richard Zemel -
2013 Oral: Annealing between distributions by averaging moments »
Roger Grosse · Chris Maddison · Russ Salakhutdinov -
2013 Poster: Latent Structured Active Learning »
Wenjie Luo · Alex Schwing · Raquel Urtasun -
2013 Poster: The Power of Asymmetry in Binary Hashing »
Behnam Neyshabur · Nati Srebro · Russ Salakhutdinov · Yury Makarychev · Payman Yadollahpour -
2012 Poster: Hamming Distance Metric Learning »
Mohammad Norouzi · Russ Salakhutdinov · David Fleet -
2012 Poster: Collaborative Ranking With 17 Parameters »
Maksims Volkovs · Richard Zemel -
2012 Poster: Bayesian n-Choose-k Models for Classification and Ranking »
Kevin Swersky · Danny Tarlow · Richard Zemel · Ryan Adams · Brendan J Frey -
2012 Poster: Deep Representations and Codes for Image Auto-Annotation »
Jamie Kiros · Csaba Szepesvari -
2012 Poster: 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model »
Sanja Fidler · Sven Dickinson · Raquel Urtasun -
2012 Poster: Matrix reconstruction with the local max norm »
Rina Foygel · Nati Srebro · Russ Salakhutdinov -
2012 Poster: Multimodal Learning with Deep Boltzmann Machines »
Nitish Srivastava · Russ Salakhutdinov -
2012 Poster: A Better Way to Pre-Train Deep Boltzmann Machines »
Russ Salakhutdinov · Geoffrey E Hinton -
2012 Poster: Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins »
Alex Schwing · Tamir Hazan · Marc Pollefeys · Raquel Urtasun -
2012 Spotlight: 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model »
Sanja Fidler · Sven Dickinson · Raquel Urtasun -
2012 Oral: Multimodal Learning with Deep Boltzmann Machines »
Nitish Srivastava · Russ Salakhutdinov -
2012 Session: Oral Session 1 »
Raquel Urtasun -
2012 Poster: Efficient Sampling for Bipartite Matching Problems »
Maksims Volkovs · Richard Zemel -
2012 Poster: Cardinality Restricted Boltzmann Machines »
Kevin Swersky · Danny Tarlow · Ilya Sutskever · Richard Zemel · Russ Salakhutdinov · Ryan Adams -
2011 Workshop: Challenges in Learning Hierarchical Models: Transfer Learning and Optimization »
Quoc V. Le · Marc'Aurelio Ranzato · Russ Salakhutdinov · Josh Tenenbaum · Andrew Y Ng -
2011 Poster: Learning to Learn with Compound HD Models »
Russ Salakhutdinov · Josh Tenenbaum · Antonio Torralba -
2011 Spotlight: Learning to Learn with Compound HD Models »
Russ Salakhutdinov · Josh Tenenbaum · Antonio Torralba -
2011 Session: Spotlight Session 5 »
Raquel Urtasun -
2011 Session: Oral Session 6 »
Raquel Urtasun -
2011 Poster: Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities »
Angela Yao · Juergen Gall · Luc V Gool · Raquel Urtasun -
2011 Poster: Joint 3D Estimation of Objects and Scene Layout »
Andreas Geiger · Christian Wojek · Raquel Urtasun -
2011 Poster: Learning with the weighted trace-norm under arbitrary sampling distributions »
Rina Foygel · Russ Salakhutdinov · Ohad Shamir · Nati Srebro -
2011 Poster: Transfer Learning by Borrowing Examples »
Joseph Lim · Russ Salakhutdinov · Antonio Torralba -
2010 Workshop: Transfer Learning Via Rich Generative Models. »
Russ Salakhutdinov · Ryan Adams · Josh Tenenbaum · Zoubin Ghahramani · Tom Griffiths -
2010 Poster: Sparse Coding for Learning Interpretable Spatio-Temporal Primitives »
Taehwan Kim · Greg Shakhnarovich · Raquel Urtasun -
2010 Poster: Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm »
Russ Salakhutdinov · Nati Srebro -
2010 Session: Spotlights Session 6 »
Raquel Urtasun -
2010 Session: Oral Session 7 »
Raquel Urtasun -
2010 Poster: Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation »
Mathieu Salzmann · Raquel Urtasun -
2010 Poster: A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction »
Tamir Hazan · Raquel Urtasun -
2010 Poster: Practical Large-Scale Optimization for Max-norm Regularization »
Jason D Lee · Benjamin Recht · Russ Salakhutdinov · Nati Srebro · Joel A Tropp -
2010 Talk: Opening Remarks and Awards »
Richard Zemel · Terrence Sejnowski · John Shawe-Taylor -
2009 Workshop: Approximate Learning of Large Scale Graphical Models »
Russ Salakhutdinov · Amir Globerson · David Sontag -
2009 Placeholder: Opening Remarks »
Richard Zemel -
2009 Poster: Evaluating multi-class learning strategies in a generative hierarchical framework for object detection »
Sanja Fidler · Marko Boben · Ales Leonardis -
2009 Poster: Replicated Softmax: an Undirected Topic Model »
Russ Salakhutdinov · Geoffrey E Hinton -
2009 Poster: Learning in Markov Random Fields using Tempered Transitions »
Russ Salakhutdinov -
2009 Poster: Modelling Relational Data using Bayesian Clustered Tensor Factorization »
Ilya Sutskever · Russ Salakhutdinov · Josh Tenenbaum -
2008 Poster: Comparing model predictions of response bias and variance in cue combination »
Rama Natarajan · Iain Murray · Ladan Shams · Richard Zemel -
2008 Poster: Learning Hybrid Models for Image Annotation with Partially Labeled Data »
Xuming He · Richard Zemel -
2008 Poster: Evaluating probabilities under high-dimensional latent variable models »
Iain Murray · Russ Salakhutdinov -
2008 Poster: Competing RBM density models for classification of fMRI images »
Tanya Schmah · Geoffrey E Hinton · Richard Zemel -
2008 Spotlight: Evaluating probabilities under high-dimensional latent variable models »
Iain Murray · Russ Salakhutdinov -
2007 Poster: Probabilistic Matrix Factorization »
Russ Salakhutdinov · Andriy Mnih -
2007 Oral: Probabilistic Matrix Factorization »
Russ Salakhutdinov · Andriy Mnih -
2007 Poster: Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes »
Russ Salakhutdinov · Geoffrey E Hinton