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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1973 1
1978 1
1982 1
1985 2
1986 2
1987 1
1988 1
1990 2
1991 3
1992 8
1993 4
1994 7
1995 10
1996 14
1997 7
1998 7
1999 16
2000 10
2001 14
2002 11
2003 8
2004 8
2005 4
2006 16
2007 12
2008 7
2009 12
2010 9
2011 9
2012 17
2013 20
2014 10
2015 12
2016 18
2017 10
2018 16
2019 10
2020 20
2021 19
2022 20
2023 24
2024 9

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388 results

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Page 1
Deep Task-Based Quantization.
Shlezinger N, Eldar YC. Shlezinger N, et al. Entropy (Basel). 2021 Jan 13;23(1):104. doi: 10.3390/e23010104. Entropy (Basel). 2021. PMID: 33450996 Free PMC article.
Quantizers play a critical role in digital signal processing systems. ...Our results indicate that, in a MIMO channel estimation setup, the proposed deep task-bask quantizer is capable of approaching the optimal performance limits dictated by indirect rate-distor …
Quantizers play a critical role in digital signal processing systems. ...Our results indicate that, in a MIMO channel estimation setu …
Transform Quantization for CNN Compression.
Young SI, Zhe W, Taubman D, Girod B. Young SI, et al. IEEE Trans Pattern Anal Mach Intell. 2022 Sep;44(9):5700-5714. doi: 10.1109/TPAMI.2021.3084839. Epub 2022 Aug 4. IEEE Trans Pattern Anal Mach Intell. 2022. PMID: 34048338
We optimally transform (decorrelate) and quantize the weights post-training using a rate-distortion framework to improve compression at any given quantization bit-rate. ...We first introduce a theory of rate and distortion for CNN quantization a …
We optimally transform (decorrelate) and quantize the weights post-training using a rate-distortion framework to improve compr …
Rate Distortion Theory for Descriptive Statistics.
Harremoës P. Harremoës P. Entropy (Basel). 2023 Mar 5;25(3):456. doi: 10.3390/e25030456. Entropy (Basel). 2023. PMID: 36981344 Free PMC article.
Rate distortion theory was developed for optimizing lossy compression of data, but it also has applications in statistics. In this paper, we illustrate how rate distortion theory can be used to analyze various datasets. The analysis involves testing, identification …
Rate distortion theory was developed for optimizing lossy compression of data, but it also has applications in statistics. In this pa …
A High-Precision Voltage-Quantization-Based Current-Mode Computing-in-Memory SRAM.
Zhao R, Gong Z, Liu Y, Chen J. Zhao R, et al. Micromachines (Basel). 2023 Nov 29;14(12):2180. doi: 10.3390/mi14122180. Micromachines (Basel). 2023. PMID: 38138349 Free PMC article.
Non-linear distortion of signals is a serious problem in computing-in-memory SRAM (CIM-SRAM) circuits in current mode. ...
Non-linear distortion of signals is a serious problem in computing-in-memory SRAM (CIM-SRAM) circuits in current mode. ...
Optimal Adaptive Quantization Based on Temporal Distortion Propagation Model for HEVC.
Bichon M, Le Tanou J, Ropert M, Hamidouche W, Morin L. Bichon M, et al. IEEE Trans Image Process. 2019 Nov;28(11):5419-5434. doi: 10.1109/TIP.2019.2919180. Epub 2019 Jun 3. IEEE Trans Image Process. 2019. PMID: 31170072 Free article.
Optimal adaptive quantization is one of the key points to optimize the coding efficiency of video encoders. ...Optimal quantizers are then designed per block in order to achieve global optimization in terms of rate-distortion efficiency. ...
Optimal adaptive quantization is one of the key points to optimize the coding efficiency of video encoders. ...Optimal quantizers …
Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.
Ki S, Bae SH, Kim M, Ko H. Ki S, et al. IEEE Trans Image Process. 2018 Jul;27(7):3178-3193. doi: 10.1109/TIP.2018.2818439. IEEE Trans Image Process. 2018. PMID: 29641399
Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. ...To our best knowledge, our paper is the first approach to automatically adjust …
Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as prep …
Optimized Product Quantization.
Ge T, He K, Ke Q, Sun J. Ge T, et al. IEEE Trans Pattern Anal Mach Intell. 2014 Apr;36(4):744-55. doi: 10.1109/TPAMI.2013.240. IEEE Trans Pattern Anal Mach Intell. 2014. PMID: 26353197
Product quantization (PQ) is an effective vector quantization method. A product quantizer can generate an exponentially large codebook at very low memory/time cost. ...In this paper, we optimize PQ by minimizing quantization distortions w.r.t th …
Product quantization (PQ) is an effective vector quantization method. A product quantizer can generate an exponentially …
Rate-distortion analysis of dead-zone plus uniform threshold scalar quantization and its application--part I: fundamental theory.
Sun J, Duan Y, Li J, Liu J, Guo Z. Sun J, et al. IEEE Trans Image Process. 2013 Jan;22(1):202-14. doi: 10.1109/TIP.2012.2215618. Epub 2012 Aug 27. IEEE Trans Image Process. 2013. PMID: 22949060
This paper provides a systematic rate-distortion (R-D) analysis of the dead-zone plus uniform threshold scalar quantization (DZ+UTSQ) with nearly uniform reconstruction quantization (NURQ) for generalized Gaussian distribution (GGD), which consists of two asp …
This paper provides a systematic rate-distortion (R-D) analysis of the dead-zone plus uniform threshold scalar quantization (D …
Information Bottleneck and Aggregated Learning.
Soflaei M, Zhang R, Guo H, Al-Bashabsheh A, Mao Y. Soflaei M, et al. IEEE Trans Pattern Anal Mach Intell. 2023 Dec;45(12):14807-14820. doi: 10.1109/TPAMI.2023.3302150. Epub 2023 Nov 3. IEEE Trans Pattern Anal Mach Intell. 2023. PMID: 37698970
We show that IB learning is, in fact, equivalent to a special class of the quantization problem. The classical results in rate-distortion theory then suggest that IB learning can benefit from a "vector quantization" approach, namely, simultaneously learning t …
We show that IB learning is, in fact, equivalent to a special class of the quantization problem. The classical results in rate-dis …
Hybrid Laplace Distribution-Based Low Complexity Rate-Distortion Optimized Quantization.
Cui J, Wang S, Wang S, Zhang X, Ma S, Gao W. Cui J, et al. IEEE Trans Image Process. 2017 Aug;26(8):3802-3816. doi: 10.1109/TIP.2017.2703112. Epub 2017 May 10. IEEE Trans Image Process. 2017. PMID: 28500003
Rate distortion optimized quantization (RDOQ) is an efficient encoder optimization method that plays an important role in improving the rate-distortion (RD) performance of the high-efficiency video coding (HEVC) codecs. However, the superior performance of RD …
Rate distortion optimized quantization (RDOQ) is an efficient encoder optimization method that plays an important role in impr …
388 results