Results 231 to 240 of about 226,838 (267)

Speech Recognition Model Compression

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Deep Neural Network-based speech recognition systems are widely used in most speech processing applications. To achieve better model robustness and accuracy, these networks are constructed with millions of parameters, making them storage and compute-intensive. In this paper, we propose Bin & Quant (B&Q), a compression technique using which we were able
Madhumitha Sakthi, Ahmed H. Tewfik, Raj Pawate   +2 more
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Model based concordance compression

Data Compression Conference, 1992., 2003
The authors discuss concordance compression using the framework now customary in compression theory. They begin by creating a mathematical model of concordance generation, and then use optimal compression engines, such as Huffman or arithmetic coding, to do the actual compression. It should be noted that in the context of a static information retrieval
Abraham Bookstein, Shmuel T. Klein, Timo Raita   +2 more
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Bayesian Automatic Model Compression

IEEE Journal of Selected Topics in Signal Processing, 2020
Model compression has drawn great attention in deep learning community. A core problem in model compression is to determine the layer-wise optimal compression policy, e.g., the layer-wise bit-width in network quantization. Conventional hand-crafted heuristics rely on human experts and are usually sub-optimal, while recent reinforcement learning based ...
Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Jian Cheng   +3 more
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Local Modeling for WebGraph Compression

2010 Data Compression Conference, 2010
We describe a simple hierarchical scheme for webgraph compression, which supports efficient in-memory and from-disk decoding of page neighborhoods, for neighborhoods defined for both incoming and outgoing links. The scheme is highly competitive in terms of both compression effectiveness and decoding speed.
Vo Ngoc Anh, Alistair Moffat
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3D model compression in MPEG

2008 15th IEEE International Conference on Image Processing, 2008
3D polygonal mesh is the most commonly used representation for 3D graphic models. Compact and compressed representation of the 3D mesh is the major functionality of MPEG 3D mesh compression technologies. 3D mesh coding (3 DMC) in MPEG was first standardized in 2000 with the achievement of compression ratio of more than 40 times with reasonable quality.
Eun-Young Chang, Namho Hur, Euee S. Jang
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Predictive modeling in XML compression

2007 2nd International Conference on Digital Information Management, 2007
Since its advent, the Extensible Markup Language (XML) has gained tremendous popularity in many different application areas. However, XML data is generally very verbose and redundant, and thus it requires a lot of disk space to store and bandwidth to transfer. To overcome this problem, many methods for compressing XML documents have been proposed.
Olli Luoma, Jukka Teuhola
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On the Compression of Markov Prediction Model

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007
Markov prediction model is the basis of Web prefetching and personalized recommendation. The existence of a large amount of Web objects results in a vast increase in the number of states which represent the users visited transfer behavior, which also causes the problem of huge spatial complexity in prediction model.
Lei Shi 0001, Yao Yao, Lin Wei
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Oldroyd Model for Compressible Fluids

Journal of Mathematical Sciences, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Learning Compressible Models

Proceedings of the 2010 SIAM International Conference on Data Mining, 2010
Yi Zhang 0010, Jeff G. Schneider, Artur Dubrawski   +2 more
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Exploration and Estimation for Model Compression

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021
Yanfu Zhang, Shangqian Gao, Heng Huang 0001   +2 more
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