Zobrazeno 1 - 10
of 297
pro vyhledávání: '"GEHRKE, JOHANNES"'
The papers in this special section were presented at the 31st International Conference on Data Engineering that was held in Seoul, Korea, on April 13-17, 2015. 17, 2015.
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82175
https://tud.qucosa.de/api/qucosa%3A82175/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82175/attachment/ATT-0/
Since its inception in 1984, the IEEE International Conference on Data Engineering (ICDE) has become a premier forum for the exchange and dissemination of data management research results among researchers, users, practitioners, and developers. Conti
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82084
https://tud.qucosa.de/api/qucosa%3A82084/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82084/attachment/ATT-0/
Autor:
Bubeck, Sébastien, Chandrasekaran, Varun, Eldan, Ronen, Gehrke, Johannes, Horvitz, Eric, Kamar, Ece, Lee, Peter, Lee, Yin Tat, Li, Yuanzhi, Lundberg, Scott, Nori, Harsha, Palangi, Hamid, Ribeiro, Marco Tulio, Zhang, Yi
Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest mo
Externí odkaz:
http://arxiv.org/abs/2303.12712
Autor:
Cutler, Ross, Hosseinkashi, Yasaman, Pool, Jamie, Filipi, Senja, Aichner, Robert, Tu, Yuan, Gehrke, Johannes
A primary goal of remote collaboration tools is to provide effective and inclusive meetings for all participants. To study meeting effectiveness and meeting inclusiveness, we first conducted a large-scale email survey (N=4,425; after filtering N=3,29
Externí odkaz:
http://arxiv.org/abs/2102.09803
Autor:
Gupchup, Jayant, Aazami, Ashkan, Fan, Yaran, Filipi, Senja, Finley, Tom, Inglis, Scott, Asteborg, Marcus, Caroll, Luke, Chari, Rajan, Cozowicz, Markus, Gopal, Vishak, Prakash, Vinod, Bendapudi, Sasikanth, Gerrits, Jack, Lau, Eric, Liu, Huazhou, Rossi, Marco, Slobodianyk, Dima, Birjukov, Dmitri, Cooper, Matty, Javar, Nilesh, Perednya, Dmitriy, Srinivasan, Sriram, Langford, John, Cutler, Ross, Gehrke, Johannes
Publikováno v:
ML for Systems, NeurIPS 2020
Large software systems tune hundreds of 'constants' to optimize their runtime performance. These values are commonly derived through intuition, lab tests, or A/B tests. A 'one-size-fits-all' approach is often sub-optimal as the best value depends on
Externí odkaz:
http://arxiv.org/abs/2011.12715
Autor:
Natarajan, Nagarajan, Karthikeyan, Ajaykrishna, Jain, Prateek, Radicek, Ivan, Rajamani, Sriram, Gulwani, Sumit, Gehrke, Johannes
We formalize and study ``programming by rewards'' (PBR), a new approach for specifying and synthesizing subroutines for optimizing some quantitative metric such as performance, resource utilization, or correctness over a benchmark. A PBR specificatio
Externí odkaz:
http://arxiv.org/abs/2007.06835
Autor:
Pool, Jamie, Beyrami, Ebrahim, Gopal, Vishak, Aazami, Ashkan, Gupchup, Jayant, Rowland, Jeff, Li, Binlong, Kanani, Pritesh, Cutler, Ross, Gehrke, Johannes
Web-scale applications can ship code on a daily to weekly cadence. These applications rely on online metrics to monitor the health of new releases. Regressions in metric values need to be detected and diagnosed as early as possible to reduce the disr
Externí odkaz:
http://arxiv.org/abs/2006.12793
Autor:
Reddy, Chandan K. A., Gopal, Vishak, Cutler, Ross, Beyrami, Ebrahim, Cheng, Roger, Dubey, Harishchandra, Matusevych, Sergiy, Aichner, Robert, Aazami, Ashkan, Braun, Sebastian, Rana, Puneet, Srinivasan, Sriram, Gehrke, Johannes
The INTERSPEECH 2020 Deep Noise Suppression (DNS) Challenge is intended to promote collaborative research in real-time single-channel Speech Enhancement aimed to maximize the subjective (perceptual) quality of the enhanced speech. A typical approach
Externí odkaz:
http://arxiv.org/abs/2005.13981
Autor:
Yang, Zongheng, Chandramouli, Badrish, Wang, Chi, Gehrke, Johannes, Li, Yinan, Minhas, Umar Farooq, Larson, Per-Åke, Kossmann, Donald, Acharya, Rajeev
Corporations today collect data at an unprecedented and accelerating scale, making the need to run queries on large datasets increasingly important. Technologies such as columnar block-based data organization and compression have become standard prac
Externí odkaz:
http://arxiv.org/abs/2004.10898
Autor:
Misra, Pulkit A., Radhakrishnan, Srihari, Chase, Jeffrey S., Gehrke, Johannes, Lebeck, Alvin R.
Distributed, transactional storage systems scale by sharding data across servers. However, workload-induced hotspots result in contention, leading to higher abort rates and performance degradation. We present KAIROS, a transactional key-value storage
Externí odkaz:
http://arxiv.org/abs/2003.04150