Publications

Found 175 results
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C
Pathak, D., Kraehenbuehl P., Yu S. X., & Darrell T. (2015).  Constrained Structured Regression with Convolutional Neural Networks. CoRR. abs/1511.07497,
Bertasius, G., Torresani L., Yu S. X., & Shi J. (2016).  Convolutional Random Walk Networks for Semantic Image Segmentation.
D
Yang, H. Hua, & Moody J. (2000).  Data Visualization and Feature Selection: New Algorithms for Nongaussian Data. 12,
Ratnasamy, S., Karp B., Shenker S. J., Estrin D., Govindan R., Yin L., et al. (2003).  Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table. 8(4), 427-442.
Ratnasamy, S., Karp B., Shenker S. J., Estrin D., Govindan R., Yin L., et al. (2003).  Data-Centric Storage in Sensornets with GHT, a Geographic Hash Table. 8(4), 427-442.
Liu, J., Shenker S. J., Schapira M., & Yang B. (2011).  Data-Driven Network Connectivity. 1-6.
Feldman, J., & Yakimovsky Y.. (1974).  Decision Theory and Artificial Intelligence: I. A Semantics-Based Region Analyzer. 5(4), 349-371.
Alizadeh, M., Yang S., Katti S., McKeown N., Prabhakar B., & Shenker S. J. (2012).  Deconstructing Datacenter Packet Transport. 133-138.
Yu, S. X., & Zipser K. (2016).  A Deep Neural Net Trained for Person Categorization Develops Both Detailed Local Features and Broad Contexual Specificities. Poster at Vision Sciences Society Annual Meeting.
Pirinen, T., Yli-Hietanen J., Pertilä P., & Visa A. (2004).  Detection and Compensation of Sensor Malfunction in Time Delay Based Direction of Arrival Estimation. Proceedings of IEEE ISCAS.
Friedland, G., Yeo C., & Hung H. (2010).  Dialocalizaton: Acoustic Speaker Diarization and Visual Localization as Joint Optimization Problem. ACM Transactions on Multimedia Computing. 6(4), 
Narihira, T., Maire M., & Yu S. X. (2015).  Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression. Proceedings of International Conference on Computer Vision.
Friedman, E., Young K., Tremper G., Liang J., Landsberg A. S., & Schuff N. (2015).  Directed Network Motifs in Alzheimer’s Disease and Mild Cognitive Impairment. PLoS ONE.
Friedman, E., Young K., Asif D., Jutla I., Liang M., Wilson S., et al. (2014).  Directed Progression Brain Networks in Alzheimer's Disease: Properties and Classification. Brain Connectivity. 4(5), 384-393.
Ben-Dor, A., Chor B., Karp R. M., & Yakhini Z. (2002).  Discovering Local Structure in Gene Expression Data: The Order Preserving Submatrix Problem. Proceedings of the Sixth Annual International Conference on Research in Computational Molecular Biology (RECOMB'02).
Ben-Dor, A., Chor B., Karp R. M., & Yakhini Z. (2003).  Discovering Local Structure in Gene Expression Data: The Order-Preserving Submatrix Problem. Journal of Computational Biology. 10(3-4), 385-398.
Yeom, S., & Tschantz M. Carl (2018).  Discriminative but Not Discriminatory: A Comparison of Fairness Definitions under Different Worldviews. Proceedings of the 2018 Workshop on Privacy in the Electronic Society. 33-41.
Vinyals, O., Deng L., Yu D., & Acero A. (2009).  Discriminative Pronunciation Learning Using Phonetic Decoder and Minimum-Classification-Error Criterion. 4445-4448.
Hornauer, S., Yellapragada B., Ranjbar A., & Yu S. X. (2019).  Driving Scene Retrieval by Example from Large-Scale Data. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition .
Hornauer, S., Yellapragada B., Ranjbar A., & Yu S. X. (2019).  Driving Scene Retrieval by Example from Large-Scale Data. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition .
Yeh, T., & Darrell T. (2008).  Dynamic Visual Category Learning.
E
Gurkan, H., Guz U., & B. Yarman S. (2007).  EEG Signal Compression Based on Classified Signature and Envelope Vector Sets. 420-423.
Yoshida, M., Ikeda C., & Suzuki H. (1994).  An Evaluation of Burst-level Bandwidth Reservation Methods in WANEnvironments.
Yang, F., Tur G., & Shriberg E. (2008).  Exploiting Dialog Act Tagging and Prosodic Information for Action Item Identification. 4941-4944.
Bertasius, G., Yu S. X., & Shi J. (2016).  Exploiting Visual-Spatial First-Person Co-Occurrence for Action-Object Detection without Labels.

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