Publications

Found 214 results
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H
Horn, G.. B., & Karp R. M. (2001).  A Maximun Likelihood Polynomial Time Syndrome Decoder to Correct Linearly Independent Errors. Proceedings of International Symposium on Information Theory.
Hopfgartner, F. (2011).  Adaptive Interactive News Video Recommendation: An Example System.
Hopfgartner, F., & Jose J. M. (2011).  Development of a Test Collection for Studying Long-Term User Modelling. Proceedings of the Workshop Information Retrieval (LWA'11).
Hopfgartner, F. (2011).  Capturing Long-Term User Interests in Online Television News Program.
Hopfgartner, F., Ren R., Urruty T., & Jose J. M. (2011).  Information Organisation Issues in Multimedia Retrieval using Low-Level Features. 241-260.
Hong, J., & Baker C. F. (2011).  How Good Is the Crowd at "Real" WSD?.
Holtz, R., Amann J., Mehani O., Wachs M., & Kaafar M. Ali (2016).  TLS in the Wild: An Internet-Wide Analysis of TLS-Based Protocols for Electronic Communication. Proceedings of the Network and Distributed System Security Symposium (NDSS).
Holtkamp, M. (1997).  Thread Migration with Active Threads.
Holmberg, M., Gelbart D., Ramacher U.., & Hemmert W. (2005).  Automatic Speech Recognition with Neural Spike Trains. Proceedings of the 9th European Conference on Speech Communication and Technology (Interspeech 2005-Eurospeech 2005).
Holmberg, M., Gelbart D., & Hemmert W. (2006).  Automatic Speech Recognition with an Adaptation Model Motivated by Auditory Processing. IEEE Transactions on Speech and Audio Processing. 14(1), 44-49.
Holmberg, M., Gelbart D., & Hemmert W. (2007).  Speech Encoding in a Model of Peripheral Auditory Processing: Quantitative Assessment by Means of Automatic Speech Recognition. Speech Communication. 49(12), 917-932.
Hölldobler, S. (1990).  CHCL - A Connectionist Inference System for Horn Logic Based on the Connection Method and using Limited Resources.
Hölldobler, S. (1990).  A Connectionist Unification Algorithm.
Hölldobler, S., & Kurfess F. (1991).  CHCL--A Connectionist Inference System.
Hofmann, T., & Puzicha J. (1998).  Unsupervised Learning from Dyadic Data.
Hoffman, J., Tzeng E., Donahue J., Jia Y., Saenko K., & Darrell T. (2014).  One-Shot Adaptation of Supervised Deep Convolutional Models.
Hoffman, J., Gupta S., & Darrell T. (2016).  Learning With Side Information Through Modality Hallucination. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 826-834.
Hoffman, J., Rodner E., Donahue J., Darrell T., & Saenko K. (2013).  Efficient Learning of Domain-Invariant Image Representations.
Hoffman, J., Guadarrama S., Tzeng E., Donahue J., Girshick R., Darrell T., et al. (2014).  Large Scale Detector Adaptation.
Hoffman, J., Darrell T., & Saenko K. (2014).  Continuous Manifold Based Adaptation for Evolving Visual Domains.
Hoffman, J., Gupta S., Leong J., Guadarrama S., & Darrell T. (2016).  Cross-modal adaptation for RGB-D detection. IEEE International Conference on Robotics and Automation (ICRA). 5032-5039.
Hoffman, J., Pathak D., Darrell T., & Saenko K. (2015).  Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2883-2891.
Hoffman, J., Pathak D., Tzeng E., Long J., Guadarrama S., Darrell T., et al. (2016).  Large Scale Visual Recognition Through Adaptation Using Joint Representation and Multiple Instance Learning. J. Mach. Learn. Res.. 17, 4954–4984.
Hoffman, J., Saenko K., Kulis B., & Darrell T. (2012).  Discovering Latent Domains for Multisource Domain Adaptation. 702-715.
Hodgkinson, L., & Karp R. M. (2011).  Algorithms to Detect Multi-Protein Modularity Conserved During Evolution.

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