Publications

Found 469 results
Author Title Type [ Year(Asc)]
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2015
Song, H. Oh, Fritz M., Göhring D., & Darrell T. (2015).  Learning to Detect Visual Grasp Affordance.
Finn, C., Tan X. Yu, Duan Y., Darrell T., Levine S., & Abbeel P. (2015).  Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders. arXiv.
Finn, C., Tan X. Yu, Duan Y., Darrell T., Levine S., & Abbeel P. (2015).  Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders. arXiv.
Donahue, J., Hendricks L. Anne, Guadarrama S., Rohrbach M., Venugopalan S., Saenko K., et al. (2015).  Long-Term Recurrent Convolutional Networks for Visual Recognition and Description.
Donahue, J., Hendricks L. Anne, Guadarrama S., Rohrbach M., Venugopalan S., Saenko K., et al. (2015).  Long-Term Recurrent Convolutional Networks for Visual Recognition and Description.
Darrell, T., Kloft M., Pontil M., Rätsch G., & Rodner E. (2015).  Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152). Dagstuhl Reports. 5, 18–55.
Narihira, T., Borth D., Yu S. X., Ni K., & Darrell T. (2015).  Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets.
Tschantz, M. Carl, Datta A., Datta A., & Wing J. M. (2015).  A Methodology for Information Flow Experiments. 2015 IEEE 28th Computer Security Foundations Symposium. 554-568.
Tschantz, M. Carl, Datta A., Datta A., & Wing J. M. (2015).  A Methodology for Information Flow Experiments. 2015 IEEE 28th Computer Security Foundations Symposium. 554-568.
Fisher, J., Darrell T., Galup L., How J., Krause A., & Soatto S. (2015).  Nonparametric Representations for Integrated Inference, Control, and Sensing.
Beijbom, O., Hoffman J., Yao E., Darrell T., Rodriguez-Ramirez A., Gonzalez-Rivero M., et al. (2015).  Quantification in-the-wild: data-sets and baselines. CoRR. abs/1510.04811,
Chu, V., McMahon I., Riano L., McDonald C. G., He Q., Perez-Tejada J. Martinez, et al. (2015).  Robotic Learning of Haptic Adjectives Through Physical Interaction. Robot. Auton. Syst.. 63(P3), 279–292.
Shelhamer, E., Barron J. T., & Darrell T. (2015).  Scene Intrinsics and Depth From a Single Image. The IEEE International Conference on Computer Vision (ICCV) Workshops.
Venugopalan, S., Rohrbach M., Donahue J., Mooney R., Darrell T., & Saenko K. (2015).  Sequence to Sequence - Video to Text. The IEEE International Conference on Computer Vision (ICCV).
Venugopalan, S., Rohrbach M., Donahue J., Mooney R., Darrell T., & Saenko K. (2015).  Sequence to Sequence - Video to Text. The IEEE International Conference on Computer Vision (ICCV).
Tzeng, E., Hoffman J., Darrell T., & Saenko K. (2015).  Simultaneous Deep Transfer Across Domains and Tasks. The IEEE International Conference on Computer Vision (ICCV). 4068-4076.
Mrowca, D., Rohrbach M., Hoffman J., Hu R., Saenko K., & Darrell T. (2015).  Spatial Semantic Regularisation for Large Scale Object Detection. The IEEE International Conference on Computer Vision (ICCV).
Andersen, D. G., Du S. S., Mahoney M., Melgaard C., Wu K., & Gu M. (2015).  Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nystrom Method.
Wang, R., Li Y., Mahoney M., & Darve E. (2015).  Structured Block Basis Factorization for Scalable Kernel Matrix Evaluation.
Tzeng, E., Devin C., Hoffman J., Finn C., Peng X., Levine S., et al. (2015).  Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. CoRR. abs/1511.07111,
Tzeng, E., Devin C., Hoffman J., Finn C., Peng X., Levine S., et al. (2015).  Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. CoRR. abs/1511.07111,
Venugopalan, S., Xu H., Donahue J., Rohrbach M., Mooney R., & Saenko K. (2015).  Translating Videos to Natural Language Using Deep Recurrent Neural Networks.
Guadarrama, S., Rodner E., Saenko K., & Darrell T. (2015).  Understanding object descriptions in robotics by open-vocabulary object retrieval and detection. The International Journal of Robotics Research. 35(1-3), 265-280.
Garg, A., Krishnan S., Murali A., Pokorny F. T., Abbeel P., Darrell T., et al. (2015).  On Visual Feature Representations for Transition State Learning in Robotic Task Demonstrations. 44,
2014
Miller, B., Kantchelian A., Afroz S., Bachwani R., Dauber E., Huang L., et al. (2014).  Adversarial Active Learning. Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop (AISec '14). 3–14.

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