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pro vyhledávání: '"Johnson, Jeff P"'
Autor:
Golden, Alicia, Hsia, Samuel, Sun, Fei, Acun, Bilge, Hosmer, Basil, Lee, Yejin, DeVito, Zachary, Johnson, Jeff, Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean
Training large-scale machine learning models poses distinct system challenges, given both the size and complexity of today's workloads. Recently, many organizations training state-of-the-art Generative AI models have reported cases of instability dur
Externí odkaz:
http://arxiv.org/abs/2405.02803
Autor:
Douze, Matthijs, Guzhva, Alexandr, Deng, Chengqi, Johnson, Jeff, Szilvasy, Gergely, Mazaré, Pierre-Emmanuel, Lomeli, Maria, Hosseini, Lucas, Jégou, Hervé
Vector databases typically manage large collections of embedding vectors. Currently, AI applications are growing rapidly, and so is the number of embeddings that need to be stored and indexed. The Faiss library is dedicated to vector similarity searc
Externí odkaz:
http://arxiv.org/abs/2401.08281
Autor:
Golden, Alicia, Hsia, Samuel, Sun, Fei, Acun, Bilge, Hosmer, Basil, Lee, Yejin, DeVito, Zachary, Johnson, Jeff, Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean
As the development of large-scale Generative AI models evolve beyond text (1D) generation to include image (2D) and video (3D) generation, processing spatial and temporal information presents unique challenges to quality, performance, and efficiency.
Externí odkaz:
http://arxiv.org/abs/2312.14385
Autor:
Lam, Maximilian, Johnson, Jeff, Xiong, Wenjie, Maeng, Kiwan, Gupta, Udit, Li, Yang, Lai, Liangzhen, Leontiadis, Ilias, Rhu, Minsoo, Lee, Hsien-Hsin S., Reddi, Vijay Janapa, Wei, Gu-Yeon, Brooks, David, Suh, G. Edward
On-device machine learning (ML) inference can enable the use of private user data on user devices without revealing them to remote servers. However, a pure on-device solution to private ML inference is impractical for many applications that rely on e
Externí odkaz:
http://arxiv.org/abs/2301.10904
Autor:
Moran, Kevin, Palacio, David N., Bernal-Cárdenas, Carlos, McCrystal, Daniel, Poshyvanyk, Denys, Shenefiel, Chris, Johnson, Jeff
Traceability is a fundamental component of the modern software development process that helps to ensure properly functioning, secure programs. Due to the high cost of manually establishing trace links, researchers have developed automated approaches
Externí odkaz:
http://arxiv.org/abs/2005.09046
Autor:
Johnson, Jeff
The logarithmic number system (LNS) is arguably not broadly used due to exponential circuit overheads for summation tables relative to arithmetic precision. Methods to reduce this overhead have been proposed, yet still yield designs with high chip ar
Externí odkaz:
http://arxiv.org/abs/2004.09313
Autor:
Johnson, Jeff
Reducing hardware overhead of neural networks for faster or lower power inference and training is an active area of research. Uniform quantization using integer multiply-add has been thoroughly investigated, which requires learning many quantization
Externí odkaz:
http://arxiv.org/abs/1811.01721
This paper aims at discovering meaningful subsets of related images from large image collections without annotations. We search groups of images related at different levels of semantic, i.e., either instances or visual classes. While k-means is usual
Externí odkaz:
http://arxiv.org/abs/1708.02898
Similarity search finds application in specialized database systems handling complex data such as images or videos, which are typically represented by high-dimensional features and require specific indexing structures. This paper tackles the problem
Externí odkaz:
http://arxiv.org/abs/1702.08734
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