Publications

Found 714 results
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Wooters, C., Mirghafori N., Stolcke A., Pirinen T., Bulyko I., Gelbart D., et al. (2004).  The 2004 ICSI-SRI-UW Meeting Recognition System. 196-208.
Wooters, C., Mirghafori N., Stolcke A., Pirinen T., Bulyko I., Gelbart D., et al. (2004).  The 2004 ICSI-SRI-UW Meeting Recognition System. 196-208.
A
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.., 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.
Graciarena, M., Delplanche M., Shriberg E., Stolcke A., & Ferrer L. (2010).  Acoustic Front-End Optimization for Bird Species Recognition. 293-296.
Mertens, R., Lei H., Gottlieb L., Friedland G., & Divakaran A. (2011).  Acoustic Super Models for Large Scale Video Event Detection.
Gomes, B., Weissman B., & Feldman J. (1998).  Active Threads: Enabling Fine-Grained Parallelism in Object-Oriented Languages. Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA ’98).
Chen, J., Zheng L., Yao Z., Wang D., Stoica I., Mahoney M., et al. (2021).  ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training.
Thomas, K., Bursztein E., Jagpal N., Rajab M. Abu, Provos N., Pearce P., et al. (2015).  Ad Injection at Scale: Assessing Deceptive Advertisement Modifications.
Thomas, K., Grier C., & Paxson V. (2012).  Adapting Social Spam Infrastructure for Political Censorship.
Encarnação, L. Miguel, & Gross M.. H. (1992).  An Adaptive Classification Scheme to Approximate Decision Boundaries Using Local Bayes Criteria - The "Melting Octree" Network.
Floyd, S., Gummadi R., & Shenker S. J. (2001).  Adaptive RED: An Algorithm for Increasing the Robustness of RED's Active Queue Management.
Goebel, C., Tribowski C., & Günther O. (2009).  Adoption of Cross-Company RFID: An Empirical Analysis of Perceived Influence Factors.
Goebel, C., Tribowski C., & Günther O. (2009).  Adoption of Cross-Company RFID: An Empirical Analysis of Perceived Influence Factors.
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.
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.
Guesgen, H. Werner, & Ladkin P. (1990).  An Algebraic Approach to General Boolean Constraint Problems.
Grigoriev, D. Yu., & Karpinski M. (1991).  Algorithms for Sparse Rational Interpolation.
Gamba, J.., Rashed M.., Razaghpanah A., Vallina-Rodriguez N., & Tapiador J.. (2020).  An Analysis of Pre-Installed Android Software. IEEE Sympsium on Security and Privacy 2020.
Govindan, R., & Radoslavov P. (2002).  An Analysis of The Internal Structure of Large Autonomous Systems.
Zhang, T.., Yao Z.., Gholami A.., Keutzer K.., Gonzalez J.., Biros G.., et al. (2019).  ANODEV2: A Coupled Neural ODE Evolution Framework. Proceedings of the 2019 NeurIPS Conference.
Zhang, T.., Yao Z.., Gholami A.., Keutzer K.., Gonzalez J.., Biros G.., et al. (2019).  ANODEV2: A Coupled Neural ODE Evolution Framework. Proceedings of the 2019 NeurIPS Conference.
Gleich, D., & Mahoney M. (2014).  Anti-Differentiating Approximation Algorithms: A Case Study with Min-Cuts, Spectral, and Flow.
Zaharia, M., Xin R. S., Wendell P., Das T., Armbrust M., Dave A., et al. (2016).  Apache Spark: a unified engine for big data processing. Communications of the ACM. 59(11), 56-65.
Zaharia, M., Xin R. S., Wendell P., Das T., Armbrust M., Dave A., et al. (2016).  Apache Spark: a unified engine for big data processing. Communications of the ACM. 59(11), 56-65.

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