Publications

Found 245 results
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G
Gildea, D., & Jurafsky D. (2001).  Automatic Labeling of Semantic Roles.
Gildea, D., & Jurafsky D. (2000).  Automatic Labeling of Semantic Roles. Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics (ACL 2000).
Gildea, D., & Hofmann T. (1999).  Topic-Based Language Models Using EM. Proceedings of the 6th European Conference on Speech Communication and Technology (Eurospeech '99).
Gildea, D., & Jurafsky D. (2000).  Automatic Labeling of Semantic Roles. The 38th Annual Meeting of the Association for Computational Linguistics (ACL-2000). 512-520.
Gilge, M., & Gusella R. (1991).  Motion Video Coding for Packet-Switching Networks -- An Integrated Approach.
Gilge, M. (1991).  Distortion Accumulation in Image Transform Coding/Decoding Cascades.
Gillick, D., Gillick L., & Wegmann S. (2011).  Don't Multiply Lightly: Quantifying Problems with the Acoustic Model Assumptions in Speech Recognition.
Gillick, D. (2010).  Can Conversational Word Usage Be Used to Predict Speaker Demographics?.
Gillick, D., Riedhammer K., Favre B., & Hakkani-Tür D. (2009).  A Global Optimization Framework for Meeting Summarization. 4769-4772.
Gillick, D., Favre B., & Hakkani-Tür D. (2008).  The ICSI Summarization System at TAC 2008.
Gillick, D., & Favre B. (2009).  A Scalable Global Model for Summarization. 10-18.
Gillick, D., Hakkani-Tür D., & Levit M. (2008).  Unsupervised Learning of Edit Parameters for Matching Name Variants. 467-470.
Gillick, D., Stafford S., & Peskin B. (2005).  Speaker Detection Without Models. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005). 757-760.
Gillick, D., Wegmann S., & Gillick L. (2012).  Discriminative Training for Speech Recognition is Compensating for Statistical Dependence on the HMM Framework. 4745-4748.
Girshick, R., Iandola F., Darrell T., & Malik J. (2015).  Deformable Part Models are Convolutional Neural Networks. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 437-446.
Girshick, R., Donahue J., Darrell T., & Malik J. (2014).  Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.
Girshick, R., Song H. Oh, & Darrell T. (2013).  Discriminatively Activated Sparselets.
Girshick, R., Donahue J., Darrell T., & Malik J. (2016).  Region-Based Convolutional Networks for Accurate Object Detection and Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 38(1), 142-158.
Gittens, A., Kottalam J., Yang J., Ringenburg M. F., Chhugani J., Racah E., et al. (2016).  A multi-platform evaluation of the randomized CX low-rank matrix factorization in Spark. Proceedings of the 5th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics.
Gittens, A.., Rothauge K.., Wang S.., Mahoney M., Gerhardt L.., Prabhat, et al. (2018).  Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. Proceedings of the 24th Annual SIGKDD. 293-301.
Gittens, A., Devarakonda A., Racah E., Ringenburg M., Gerhardt L., Kottalam J., et al. (2016).  Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
Gittens, A.., Rothauge K.., Mahoney M., Wang S.., Gerhardt L.., Prabhat, et al. (2018).  Alchemist: An Apache Spark <=> MPI Interface. Concurrency and Computation: Practice and Experience (Special Issue of the Cray User Group, CUG 2018), e5026.
Gleich, D., & Mahoney M. (2016).  Mining Large graphs. Handbook of Big Data. 191-220.
Gleich, D., & Mahoney M. (2014).  Anti-Differentiating Approximation Algorithms: A Case Study with Min-Cuts, Spectral, and Flow.
Gleich, D., & Mahoney M. (2015).  Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms. Proceedings of the 21st Annual SIGKDD.

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