From mboxrd@z Thu Jan 1 00:00:00 1970 X-Spam-Checker-Version: SpamAssassin 3.4.4 (2020-01-24) on polar.synack.me X-Spam-Level: X-Spam-Status: No, score=-1.9 required=5.0 tests=BAYES_00 autolearn=unavailable autolearn_force=no version=3.4.4 Path: eternal-september.org!reader01.eternal-september.org!reader02.eternal-september.org!feeder.eternal-september.org!aioe.org!.POSTED!not-for-mail From: "Dmitry A. Kazakov" Newsgroups: comp.lang.ada Subject: Re: Killing software and certification Date: Wed, 28 Mar 2018 21:35:26 +0200 Organization: Aioe.org NNTP Server Message-ID: References: <9ed9edb1-3342-4644-89e8-9bcf404970ee@googlegroups.com> <26a1fe54-750c-45d7-9006-b6fecaa41176@googlegroups.com> <656fb1d7-48a4-40fd-bc80-10ba9c4ad0a4@googlegroups.com> NNTP-Posting-Host: kQkuQcRDy1QFvWpyB1foYw.user.gioia.aioe.org Mime-Version: 1.0 Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 7bit X-Complaints-To: abuse@aioe.org User-Agent: Mozilla/5.0 (Windows NT 10.0; WOW64; rv:52.0) Gecko/20100101 Thunderbird/52.6.0 X-Notice: Filtered by postfilter v. 0.8.3 Content-Language: en-US Xref: reader02.eternal-september.org comp.lang.ada:51244 Date: 2018-03-28T21:35:26+02:00 List-Id: On 2018-03-28 19:06, Alejandro R. Mosteo wrote: > This line of thinking is often brought by a colleague working on > "classical" solutions to problems that are nowadays trendy on deep > learning circles. When feeling optimistic I see it as the complexity of > the simplex method: linear on average but worst case exponential. I tend > to think that the same you could have a watchdog for a stray simplex, > you could have some fallback for a DNN behaving badly (if you can detect > it in the first place :P). If you are sure that it converges to the "right" thing. Does it? How do you know when the "right thing" is not even defined? > In other words: if DNNs prove to be as useful as they promise, they'll > find a way to statistically cover the desired percent of reliability. > Maybe this is another field of research in the making. Huh, you cannot use mathematical statistics here. You don't know what are elementary events here. You cannot use models because any sample set will be too small for testing any hypothesis. That is for the case of using brute force. In other words, to make mathematical statistics work there must some solid set of known laws describing things, but there is none. > I'm also told > that "we solve X with a DNN" is no longer acceptable in the main > conferences, that you have to also provide some insight on the DNN > workings. But this is hearsay that I pass along. This is another can of worms: knowledge extraction. If you can extract knowledge from the trained system, then you can build another system based on that knowledge that would deploy a direct decision making method without any training. If you cannot, you still have no idea what the system does now and what it will do next time. -- Regards, Dmitry A. Kazakov http://www.dmitry-kazakov.de