tag:blogger.com,1999:blog-5880610.post6327628413290286368..comments2024-01-13T18:57:18.243-05:00Comments on Information Processing: Beyond Bayes: causality vs correlationSteve Hsuhttp://www.blogger.com/profile/02428333897272913660noreply@blogger.comBlogger10125tag:blogger.com,1999:blog-5880610.post-59551009443817445532010-07-17T12:32:02.358-04:002010-07-17T12:32:02.358-04:00I have two issues:
1) I've always felt thinki...I have two issues:<br /><br />1) I've always felt thinking in quantum mechanics at least overlaps with thinking in a Bayesian sense, or at least the weaker mode of thinking in the language of probabilities (uh say... wave functions?), and the "cleaner" causal model is basically what happens when lots of these probabilities get sent close to 0 or 1 (I know this is an Yan Zhanghttp://concretenonsense.wordpress.com/noreply@blogger.comtag:blogger.com,1999:blog-5880610.post-57822682091905437682010-07-17T12:31:44.110-04:002010-07-17T12:31:44.110-04:00I have two issues:
1) I've always felt thinki...I have two issues:<br /><br />1) I've always felt thinking in quantum mechanics at least overlaps with thinking in a Bayesian sense, or at least the weaker mode of thinking in the language of probabilities (uh say... wave functions?), and the "cleaner" causal model is basically what happens when lots of these probabilities get sent close to 0 or 1 (I know this is an Yan Zhanghttp://concretenonsense.wordpress.com/noreply@blogger.comtag:blogger.com,1999:blog-5880610.post-64416435310581389672010-07-13T10:45:16.524-04:002010-07-13T10:45:16.524-04:00I think what Pearl did is nice, but closer to inve...I think what Pearl did is nice, but closer to inventing a notation than to solving any fundamental problem.<br /><br />I notice no one has commented on his third assertion, which relates to whether to Bayesians must agree in the limit of infinite shared data. (Aumann agreement theorem, intersubjective agreement, yada yada.)steve hsuhttp://duende.uoregon.edu/noreply@blogger.comtag:blogger.com,1999:blog-5880610.post-66467057747523946352010-07-12T17:55:41.991-04:002010-07-12T17:55:41.991-04:00Remember Daniel Pearl - the reporter who got his h...Remember Daniel Pearl - the reporter who got his head cut off after being kidnapped in Pakistan? That's Judea Pearl's son. If you look at the dedication in "Causality", it says something like "for my wonderful Danny".Eric Fossnoreply@blogger.comtag:blogger.com,1999:blog-5880610.post-62276736026290225932010-07-10T22:17:08.518-04:002010-07-10T22:17:08.518-04:00It seems to me that anyone who examines everyday c...It seems to me that anyone who examines everyday causal reasoning ought to spend a significant effort considering its relationship(s) to careful analysis using the laws of physics. It is rather ironic that from a physicist's point of view, everyday causal reasoning is not fundamental, rigorous, or even particularly clear and coherent in many (most?) cases. I should elaborate on this a bit, CWnoreply@blogger.comtag:blogger.com,1999:blog-5880610.post-55047796835875937632010-07-10T17:11:13.766-04:002010-07-10T17:11:13.766-04:00http://cscs.umich.edu/~crshalizi/weblog/664.html -...http://cscs.umich.edu/~crshalizi/weblog/664.html - "Praxis and Ideology in Bayesian Data Analysis"<br /><br />cosma shalizi going off on bayesians :P<br /><br />cheers!glorynoreply@blogger.comtag:blogger.com,1999:blog-5880610.post-42615021524876776622010-07-10T14:39:33.461-04:002010-07-10T14:39:33.461-04:00Hye, I very much agree with the last part. Probabi...Hye, I very much agree with the last part. Probability theory is really just glorified counting. The hard part is to know what (not) to count. Anyway, nothing forbids us to focus on counting "events of type Y which occurred after we did X", and thus getting into probabilistic statements about "causes".<br /><br />My impression is that Pearl has fallen in love with his ideas sosilkophttp://cleeray.myopenid.com/noreply@blogger.comtag:blogger.com,1999:blog-5880610.post-54177200079197443042010-07-10T13:50:09.779-04:002010-07-10T13:50:09.779-04:00I find Pearl's claims about the "lack of ...I find Pearl's claims about the "lack of expressiveness" of probability distributions for "causal" knowledge unfortunate. Of course you can put up a probability distribution that shows that "symptoms do not cause disease". It's just that it doesn't suffice to examine "the population with symptoms" and "the population with disease" silkophttp://cleeray.myopenid.com/noreply@blogger.comtag:blogger.com,1999:blog-5880610.post-78575589068544923782010-07-10T13:14:37.916-04:002010-07-10T13:14:37.916-04:00Steve, your first link to Pearl's paper is mis...Steve, your first link to Pearl's paper is missing an "h" at the beginning.Ben Espenhttp://www.benespen.com/noreply@blogger.comtag:blogger.com,1999:blog-5880610.post-74191418190564093482010-07-10T13:11:13.898-04:002010-07-10T13:11:13.898-04:00definitely provocative -- Even the example you gav...definitely provocative -- Even the example you gave above has pretty big holes in it. I think a lot of issues stem back to semantics and how prior knowledge is cast. When he claims that "mud does not cause rain" is a "fact", it assumes definitions for "fact" and "cause" that may preclude expressing that statement using standard probability. MY Hyenoreply@blogger.com