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A robot operating in a real-world environment needs to perform reasoning over a variety of sensor modalities such as vision, language and motion trajectories.
K. Q. Weinberger, J. Blitzer, and L. K. Saul, “Distance metric learning for large margin nearest neighbor classification,” in NIPS , 2005
2005
Earlier work this paper cites.
I. Tsochantaridis, T. Joachims, T. Hofmann, Y. Altun, and Y. Singer, “Large margin methods for structured and interdependent output variables.” JMLR , vol. 6, no. 9, 2005
2005
Earlier work this paper cites.
G. Hinton and R. Salakhutdinov, “Reducing the dimensionality of data with neural networks,” Science , vol. 313, no. 5786, pp. 504–507, 2006
2006
Earlier work this paper cites.
R. Hadsell, A. Erkan, P. Sermanet, M. Scoffier, U. Muller, and Y. LeCun, “Deep belief net learning in a long-range vision system for autonomous off-road driving,” in IROS , 2008
2008
Earlier work this paper cites.
P. Vincent, H. Larochelle, Y. Bengio, et al. , “Extracting and composing robust features with denoising autoencoders,” in ICML , 2008
2008
Earlier work this paper cites.
L. Van der Maaten and G. Hinton, “Visualizing data using t-sne,” JMLR , vol. 9, no. 2579-2605, p. 85, 2008
2008
Earlier work this paper cites.
I. Goodfellow, Q. Le, A. Saxe, H. Lee, and A. Y. Ng, “Measuring invariances in deep networks,” in NIPS , 2009
2009
Earlier work this paper cites.
M. Quigley, K. Conley, B. Gerkey, et al. , “Ros: an open-source robot operating system,” in ICRA workshop on open source software , 2009
2009
Earlier work this paper cites.
R. B. Rusu, “Semantic 3d object maps for everyday manipulation in human living environments,” KI-Künstliche Intelligenz , 2010
2010
Earlier work this paper cites.
R. Socher, J. Pennington, E. Huang, A. Ng, and C. Manning, “Semi-supervised recursive autoencoders for predicting sentiment distributions,” in EMNLP , 2011
2011
Earlier work this paper cites.
J. Weston, S. Bengio, and N. Usunier, “Wsabie: Scaling up to large vocabulary image annotation,” in IJCAI , 2011
2011
Earlier work this paper cites.
J. Ngiam, A. Khosla, M. Kim, J. Nam, H. Lee, and A. Y. Ng, “Multimodal deep learning,” in ICML , 2011
2011
Earlier work this paper cites.
M. Bollini, J. Barry, and D. Rus, “Bakebot: Baking cookies with the pr2,” in IROS PR2 Workshop , 2011
2011
Cited alongside, same era.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in NIPS , 2012
2012
Cited alongside, same era.
N. Srivastava and R. R. Salakhutdinov, “Multimodal learning with deep boltzmann machines,” in NIPS , 2012
2012
Cited alongside, same era.
J. Moore, S. Chen, T. Joachims, and D. Turnbull, “Learning to embed songs and tags for playlist prediction,” in ISMIR , 2012
2012
Cited alongside, same era.
S. Miller, J. Van Den Berg, M. Fritz, T. Darrell, K. Goldberg, and P. Abbeel, “A geometric approach to robotic laundry folding,” IJRR , 2012
2012
Cited alongside, same era.
G. Erdogan, I. Yildirim, and R. A. Jacobs, “Transfer of object shape knowledge across visual and haptic modalities,” in Proceedings of the 36th Annual Conference of the Cognitive Science Society , 2014
2014
Later among the works it cites.
M. Muja and D. G. Lowe, “Scalable nearest neighbor algorithms for high dimensional data,” PAMI , 2014
2014
Later among the works it cites.
K. Sohn, W. Shang, and H. Lee, “Improved multimodal deep learning with variation of information,” in NIPS , 2014
2014
Later among the works it cites.
J. Hu, J. Lu, and Y.-P. Tan, “Discriminative deep metric learning for face verification in the wild,” in CVPR , 2014
2014
Later among the works it cites.
J. Sung, B. Selman, and A. Saxena, “Synthesizing manipulation sequences for under-specified tasks using unrolled markov random fields,” in IROS , 2014
2014
Later among the works it cites.
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O. Kroemer, E. Ugur, E. Oztop, and J. Peters, “A kernel-based approach to direct action perception,” in ICRA , 2012
2012
Cited alongside, same era.
M. D. Zeiler, “Adadelta: An adaptive learning rate method,” arXiv preprint arXiv:1212.5701 , 2012
2012
Cited alongside, same era.
Y. Ioannou, B. Taati, R. Harrap, et al. , “Difference of normals as a multi-scale operator in unorganized point clouds,” in 3DIMPVT , 2012
2012
Cited alongside, same era.
F. Bastien, P. Lamblin, R. Pascanu, et al. , “Theano: new features and speed improvements,” Deep Learning and Unsupervised Feature Learning NIPS 2012 Workshop, 2012
2012
Cited alongside, same era.
T. Mikolov, Q. V. Le, and I. Sutskever, “Exploiting similarities among languages for machine translation.” CoRR , 2013
2013
Cited alongside, same era.
I. Lenz, H. Lee, and A. Saxena, “Deep learning for detecting robotic grasps,” RSS , 2013
2013
Cited alongside, same era.
M. D. Zeiler, M. Ranzato, R. Monga, et al. , “On rectified linear units for speech processing,” in ICASSP , 2013
2013
Cited alongside, same era.
D. Misra, J. Sung, K. Lee, and A. Saxena, “Tell me dave: Context-sensitive grounding of natural language to mobile manipulation instructions,” in RSS , 2014
2014
Later among the works it cites.
J. Sung, S. H. Jin, and A. Saxena, “Robobarista: Object part-based transfer of manipulation trajectories from crowd-sourcing in 3d pointclouds,” in International Symposium on Robotics Research , 2015
2015
Closest in time.
M. Koval, N. Pollard , and S. Srinivasa, “Pre- and post-contact policy decomposition for planar contact manipulation under uncertainty,” International Journal of Robotics Research , August 2015
2015
Closest in time.
D. Kappler, P. Pastor, M. Kalakrishnan, M. Wuthrich, and S. Schaal, “Data-driven online decision making for autonomous manipulation,” in R:SS , 2015
2015
Closest in time.
D. Kappler, J. Bohg, and S. Schaal, “Leveraging big data for grasp planning,” in ICRA , 2015
2015
Closest in time.
S. Levine, N. Wagener, and P. Abbeel, “Learning contact-rich manipulation skills with guided policy search,” ICRA , 2015
2015
Closest in time.
I. Lenz, R. Knepper, and A. Saxena, “Deepmpc: Learning deep latent features for model predictive control,” in RSS , 2015
2015
Closest in time.