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  • Bijective BWT (6 Comments)

    David Scott has written a bijective BWT transform, which brings all the advantages of bijectiveness to BWT based compressors. Among other things, making BWT more suitable for compression-before-encryption and also give (slightly) better compression.

  • Asymmetric Binary System (113 Comments)

    Jarek Duda’s “Asymmetric Binary System” promises to be an alternate to arithmetic coding, having all the advantages, but being much simpler. Matt has coded a PAQ based compressor using ABS for back-end encoding. Update: Andrew Polar has written an alternate implementation of ABS.

  • Precomp: More Compression for your Compressed Files (3 Comments)

    So many of today’s files are already compressed (using old, outdated algorithms) that newer algorithms don’t even get a chance to touch them. Christian Schneider’s Precomp comes to rescue by undoing the harm.

  • On2 Technologies is Hiring

    There aren’t too many companies working on cutting edge codecs, and of those few this one is hiring. Best of luck.

  • China’s AVS Specifications Available (2 Comments)

    Its old news that China has developed their own Advanced Video Standard to avoid high licensing fees. English translation of the standard is now available, along with the IPR policy. Finally something technical that you can get your hands on to feed your appetite.

Risks and Rewards

Posted by Sachin Garg on 30th November 2005 | Permanent Link

After reading the very refreshing article pointed by Mark Nelson where John Allen Paulos takes us on a tour starting with complexity and ending with incompleteness, I went on to read some more from the archive.

I came across this more recent article on Risks and Rewards and how humans percieve it, here John explains how we usually choose the more certain scenario even when mathematical probability of two events is same.

It made me wonder if human bias towards more certain options has limited the optimizations we apply to improve PPM models for predicting the next symbols. Has our bias towards more certian models reduced the risks our algorithms take and thus reduced the rewards we get?

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This entry was posted on Wednesday, November 30th, 2005 at 10:13 am by Sachin Garg. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.