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r/MachineLearning· /u/keep_up_sharma·· 3 小时前AI 评分69

learnc:用数据拟合现有 C 代码中的常量,JPEG 体积缩小 9.1%

learnc: fit the constants in existing C code to data (9.1% smaller JPEGs, +4.9 F1 on WebRTC VAD) [P]

AI 导读

learnc 能针对用户用 C 编写的评分函数,调优未经修改的 C 代码中的具名常量,并把新值写回同一文件。

正文
learnc: fit the constants in existing C code to data (9.1% smaller JPEGs, +4.9 F1 on WebRTC VAD) [P]

learnc tunes named constants in unmodified C code against a score function you write in C, and writes the same file back with new values.

Results, both on held-out data:

  • JPEG, stb_image_write.h (128 quantization-table entries, tuned on 12 Kodak images, tested on the other 12): 9.1% BD-rate at equal SSIM, checked independently in libjpeg with scikit-image. mozjpeg's tables get 2.7%. See image 1.
  • Google's WebRTC VAD (every constant in vad_core.c, tuned on LibriParty dev): F1 0.810 to 0.859 on LibriParty eval. See image 2.

Limits:

  • No JPEG gain below 1 bpp.
  • Best for tens to hundreds of constants, not large weight sets.

Code (MIT): https://github.com/devanmolsharma/learnc ·

submitted by /u/keep_up_sharma
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来源:r/MachineLearning · reddit.com