Hello Chris. Have you been applying relational learning to your Neural Crest Migration Patterns in Craniofacial Development research project? It could enhance your insights.
On Friday, September 2, 2016 at 6:18:15 AM UTC-3, Chris Rackauckas wrote: > > This entire thread is a trip... a trip which is not really relevant to > julia-users. You may want to share these musings in the form of a blog > instead of posting them here. > > On Friday, September 2, 2016 at 1:41:03 AM UTC-7, Kevin Liu wrote: >> >> Princeton's post: >> http://www.nytimes.com/2016/08/28/world/europe/france-burkini-bikini-ban.html?_r=1 >> >> Only logic saves us from paradox. - Minsky >> >> On Thursday, August 25, 2016 at 10:18:27 PM UTC-3, Kevin Liu wrote: >>> >>> Tim Holy, I am watching your keynote speech at JuliaCon 2016 where you >>> mention the best optimization is not doing the computation at all. >>> >>> Domingos talks about that in his book, where an efficient kind of >>> learning is by analogy, with no model at all, and how numerous scientific >>> discoveries have been made that way, e.g. Bohr's analogy of the solar >>> system to the atom. Analogizers learn by hypothesizing that entities with >>> similar known properties have similar unknown ones. >>> >>> MLN can reproduce structure mapping, which is the more powerful type of >>> analogy, that can make inferences from one domain (solar system) to another >>> (atom). This can be done by learning formulas that don't refer to any of >>> the specific relations in the source domain (general formulas). >>> >>> Seth and Tim have been helping me a lot with putting the pieces together >>> for MLN in the repo I created >>> <https://github.com/hpoit/Kenya.jl/issues/2>, and more help is always >>> welcome. I would like to write MLN in idiomatic Julia. My question at the >>> moment to you and the community is how to keep mappings of first-order >>> harmonic functions type-stable in Julia? I am just getting acquainted with >>> the type field. >>> >>> On Tuesday, August 9, 2016 at 9:02:25 AM UTC-3, Kevin Liu wrote: >>>> >>>> Helping me separate the process in parts and priorities would be a lot >>>> of help. >>>> >>>> On Tuesday, August 9, 2016 at 8:41:03 AM UTC-3, Kevin Liu wrote: >>>>> >>>>> Tim Holy, what if I could tap into the well of knowledge that you are >>>>> to speed up things? Can you imagine if every learner had to start without >>>>> priors? >>>>> >>>>> > On Aug 9, 2016, at 07:06, Tim Holy <[email protected]> wrote: >>>>> > >>>>> > I'd recommend starting by picking a very small project. For example, >>>>> fix a bug >>>>> > or implement a small improvement in a package that you already find >>>>> useful or >>>>> > interesting. That way you'll get some guidance while making a >>>>> positive >>>>> > contribution; once you know more about julia, it will be easier to >>>>> see your >>>>> > way forward. >>>>> > >>>>> > Best, >>>>> > --Tim >>>>> > >>>>> >> On Monday, August 8, 2016 8:22:01 PM CDT Kevin Liu wrote: >>>>> >> I have no idea where to start and where to finish. Founders' help >>>>> would be >>>>> >> wonderful. >>>>> >> >>>>> >>> On Tuesday, August 9, 2016 at 12:19:26 AM UTC-3, Kevin Liu wrote: >>>>> >>> After which I have to code Felix into Julia, a relational >>>>> optimizer for >>>>> >>> statistical inference with Tuffy < >>>>> http://i.stanford.edu/hazy/tuffy/> >>>>> >>> inside, for enterprise settings. >>>>> >>> >>>>> >>>> On Tuesday, August 9, 2016 at 12:07:32 AM UTC-3, Kevin Liu wrote: >>>>> >>>> Can I get tips on bringing Alchemy's optimized Tuffy >>>>> >>>> <http://i.stanford.edu/hazy/tuffy/> in Java to Julia while >>>>> showing the >>>>> >>>> best of Julia? I am going for the most correct way, even if it >>>>> means >>>>> >>>> coding >>>>> >>>> Tuffy into C and Julia. >>>>> >>>> >>>>> >>>>> On Sunday, August 7, 2016 at 8:34:37 PM UTC-3, Kevin Liu wrote: >>>>> >>>>> I'll try to build it, compare it, and show it to you guys. I >>>>> offered to >>>>> >>>>> do this as work. I am waiting to see if they will accept it. >>>>> >>>>> >>>>> >>>>>> On Sunday, August 7, 2016 at 6:15:50 PM UTC-3, Stefan Karpinski >>>>> wrote: >>>>> >>>>>> Kevin, as previously requested by Isaiah, please take this to >>>>> some >>>>> >>>>>> other forum or maybe start a blog. >>>>> >>>>>> >>>>> >>>>>>> On Sat, Aug 6, 2016 at 10:53 PM, Kevin Liu <[email protected]> >>>>> wrote: >>>>> >>>>>>> Symmetry-based learning, Domingos, 2014 >>>>> >>>>>>> >>>>> https://www.microsoft.com/en-us/research/video/symmetry-based-learning >>>>> >>>>>>> / >>>>> >>>>>>> >>>>> >>>>>>> Approach 2: Deep symmetry networks generalize convolutional >>>>> neural >>>>> >>>>>>> networks by tying parameters and pooling over an arbitrary >>>>> symmetry >>>>> >>>>>>> group, >>>>> >>>>>>> not just the translation group. In preliminary experiments, >>>>> they >>>>> >>>>>>> outperformed convnets on a digit recognition task. >>>>> >>>>>>> >>>>> >>>>>>>> On Friday, August 5, 2016 at 4:56:45 PM UTC-3, Kevin Liu >>>>> wrote: >>>>> >>>>>>>> Minsky died of a cerebral hemorrhage at the age of 88.[40] >>>>> >>>>>>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-40> >>>>> Ray >>>>> >>>>>>>> Kurzweil <https://en.wikipedia.org/wiki/Ray_Kurzweil> says >>>>> he was >>>>> >>>>>>>> contacted by the cryonics organization Alcor Life Extension >>>>> >>>>>>>> Foundation >>>>> >>>>>>>> < >>>>> https://en.wikipedia.org/wiki/Alcor_Life_Extension_Foundation> >>>>> >>>>>>>> seeking >>>>> >>>>>>>> Minsky's body.[41] >>>>> >>>>>>>> < >>>>> https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-Kurzweil-41> >>>>> >>>>>>>> Kurzweil believes that Minsky was cryonically preserved by >>>>> Alcor and >>>>> >>>>>>>> will be revived by 2045.[41] >>>>> >>>>>>>> < >>>>> https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-Kurzweil-41> >>>>> >>>>>>>> Minsky >>>>> >>>>>>>> was a member of Alcor's Scientific Advisory Board >>>>> >>>>>>>> <https://en.wikipedia.org/wiki/Advisory_Board>.[42] >>>>> >>>>>>>> < >>>>> https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-AlcorBoard-42> >>>>> >>>>>>>> In >>>>> >>>>>>>> keeping with their policy of protecting privacy, Alcor will >>>>> neither >>>>> >>>>>>>> confirm >>>>> >>>>>>>> nor deny that Alcor has cryonically preserved Minsky.[43] >>>>> >>>>>>>> <https://en.wikipedia.org/wiki/Marvin_Minsky#cite_note-43> >>>>> >>>>>>>> >>>>> >>>>>>>> We better do a good job. >>>>> >>>>>>>> >>>>> >>>>>>>>> On Friday, August 5, 2016 at 4:45:42 PM UTC-3, Kevin Liu >>>>> wrote: >>>>> >>>>>>>>> *So, I think in the next 20 years (2003), if we can get rid >>>>> of all >>>>> >>>>>>>>> of the traditional approaches to artificial intelligence, >>>>> like >>>>> >>>>>>>>> neural nets >>>>> >>>>>>>>> and genetic algorithms and rule-based systems, and just turn >>>>> our >>>>> >>>>>>>>> sights a >>>>> >>>>>>>>> little bit higher to say, can we make a system that can use >>>>> all >>>>> >>>>>>>>> those >>>>> >>>>>>>>> things for the right kind of problem? Some problems are good >>>>> for >>>>> >>>>>>>>> neural >>>>> >>>>>>>>> nets; we know that others, neural nets are hopeless on them. >>>>> Genetic >>>>> >>>>>>>>> algorithms are great for certain things; I suspect I know >>>>> what >>>>> >>>>>>>>> they're bad >>>>> >>>>>>>>> at, and I won't tell you. (Laughter)* - Minsky, founder of >>>>> CSAIL >>>>> >>>>>>>>> MIT >>>>> >>>>>>>>> >>>>> >>>>>>>>> *Those programmers tried to find the single best way to >>>>> represent >>>>> >>>>>>>>> knowledge - Only Logic protects us from paradox.* - Minsky >>>>> (see >>>>> >>>>>>>>> attachment from his lecture) >>>>> >>>>>>>>> >>>>> >>>>>>>>>> On Friday, August 5, 2016 at 8:12:03 AM UTC-3, Kevin Liu >>>>> wrote: >>>>> >>>>>>>>>> Markov Logic Network is being used for the continuous >>>>> development >>>>> >>>>>>>>>> of drugs to cure cancer at MIT's CanceRX < >>>>> http://cancerx.mit.edu/>, >>>>> >>>>>>>>>> on >>>>> >>>>>>>>>> DARPA's largest AI project to date, Personalized Assistant >>>>> that >>>>> >>>>>>>>>> Learns (PAL) <https://pal.sri.com/>, progenitor of Siri. >>>>> One of >>>>> >>>>>>>>>> Alchemy's largest applications to date was to learn a >>>>> semantic >>>>> >>>>>>>>>> network >>>>> >>>>>>>>>> (knowledge graph as Google calls it) from the web. >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> Some on Probabilistic Inductive Logic Programming / >>>>> Probabilistic >>>>> >>>>>>>>>> Logic Programming / Statistical Relational Learning from >>>>> CSAIL >>>>> >>>>>>>>>> < >>>>> http://people.csail.mit.edu/kersting/ecmlpkdd05_pilp/pilp_ida2005_ >>>>> >>>>>>>>>> tut.pdf> (my understanding is Alchemy does PILP from >>>>> entailment, >>>>> >>>>>>>>>> proofs, and >>>>> >>>>>>>>>> interpretation) >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> The MIT Probabilistic Computing Project (where there is >>>>> Picture, an >>>>> >>>>>>>>>> extension of Julia, for computer vision; Watch the video >>>>> from >>>>> >>>>>>>>>> Vikash) >>>>> >>>>>>>>>> <http://probcomp.csail.mit.edu/index.html> >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> Probabilistic programming could do for Bayesian ML what >>>>> Theano has >>>>> >>>>>>>>>> done for neural networks. >>>>> >>>>>>>>>> <http://www.inference.vc/deep-learning-is-easy/> - Ferenc >>>>> Huszár >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> Picture doesn't appear to be open-source, even though its >>>>> Paper is >>>>> >>>>>>>>>> available. >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> I'm in the process of comparing the Picture Paper and >>>>> Alchemy code >>>>> >>>>>>>>>> and would like to have an open-source PILP from Julia that >>>>> combines >>>>> >>>>>>>>>> the >>>>> >>>>>>>>>> best of both. >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> On Wednesday, August 3, 2016 at 5:01:02 PM UTC-3, Christof >>>>> Stocker >>>>> >>>>>>>>>> >>>>> >>>>>>>>>> wrote: >>>>> >>>>>>>>>>> This sounds like it could be a great contribution. I shall >>>>> keep a >>>>> >>>>>>>>>>> curious eye on your progress >>>>> >>>>>>>>>>> >>>>> >>>>>>>>>>> Am Mittwoch, 3. August 2016 21:53:54 UTC+2 schrieb Kevin >>>>> Liu: >>>>> >>>>>>>>>>>> Thanks for the advice Cristof. I am only interested in >>>>> people >>>>> >>>>>>>>>>>> wanting to code it in Julia, from R by Domingos. The algo >>>>> has >>>>> >>>>>>>>>>>> been >>>>> >>>>>>>>>>>> successfully applied in many areas, even though there are >>>>> many >>>>> >>>>>>>>>>>> other areas >>>>> >>>>>>>>>>>> remaining. >>>>> >>>>>>>>>>>> >>>>> >>>>>>>>>>>> On Wed, Aug 3, 2016 at 4:45 PM, Christof Stocker < >>>>> >>>>>>>>>>>> >>>>> >>>>>>>>>>>> [email protected]> wrote: >>>>> >>>>>>>>>>>>> Hello Kevin, >>>>> >>>>>>>>>>>>> >>>>> >>>>>>>>>>>>> Enthusiasm is a good thing and you should hold on to >>>>> that. But >>>>> >>>>>>>>>>>>> to save yourself some headache or disappointment down >>>>> the road I >>>>> >>>>>>>>>>>>> advice a >>>>> >>>>>>>>>>>>> level head. Nothing is really as bluntly obviously >>>>> solved as it >>>>> >>>>>>>>>>>>> may seems >>>>> >>>>>>>>>>>>> at first glance after listening to brilliant people >>>>> explain >>>>> >>>>>>>>>>>>> things. A >>>>> >>>>>>>>>>>>> physics professor of mine once told me that one of the >>>>> (he >>>>> >>>>>>>>>>>>> thinks) most >>>>> >>>>>>>>>>>>> malicious factors to his past students progress where >>>>> overstated >>>>> >>>>>>>>>>>>> results/conclusions by other researches (such as >>>>> premature >>>>> >>>>>>>>>>>>> announcements >>>>> >>>>>>>>>>>>> from CERN). I am no mathematician, but as far as I can >>>>> judge is >>>>> >>>>>>>>>>>>> the no free >>>>> >>>>>>>>>>>>> lunch theorem of pure mathematical nature and not >>>>> something >>>>> >>>>>>>>>>>>> induced >>>>> >>>>>>>>>>>>> empirically. These kind of results are not that easily >>>>> to get >>>>> >>>>>>>>>>>>> rid of. If >>>>> >>>>>>>>>>>>> someone (especially an expert) states such a theorem >>>>> will prove >>>>> >>>>>>>>>>>>> wrong I >>>>> >>>>>>>>>>>>> would be inclined to believe that he is not talking >>>>> about >>>>> >>>>>>>>>>>>> literally, but >>>>> >>>>>>>>>>>>> instead is just trying to make a point about a more or >>>>> less >>>>> >>>>>>>>>>>>> practical >>>>> >>>>>>>>>>>>> implication. >>>>> >>>>>>>>>>>>> >>>>> >>>>>>>>>>>>> Am Mittwoch, 3. August 2016 21:27:05 UTC+2 schrieb Kevin >>>>> Liu: >>>>> >>>>>>>>>>>>>> The Markov logic network represents a probability >>>>> distribution >>>>> >>>>>>>>>>>>>> over the states of a complex system (i.e. a cell), >>>>> comprised of >>>>> >>>>>>>>>>>>>> entities, >>>>> >>>>>>>>>>>>>> where logic formulas encode the dependencies between >>>>> them. >>>>> >>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>> On Wednesday, August 3, 2016 at 4:19:09 PM UTC-3, Kevin >>>>> Liu >>>>> >>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>> wrote: >>>>> >>>>>>>>>>>>>>> Alchemy is like an inductive Turing machine, to be >>>>> programmed >>>>> >>>>>>>>>>>>>>> to learn broadly or restrictedly. >>>>> >>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>> The logic formulas from rules through which it >>>>> represents can >>>>> >>>>>>>>>>>>>>> be inconsistent, incomplete, or even incorrect-- the >>>>> learning >>>>> >>>>>>>>>>>>>>> and >>>>> >>>>>>>>>>>>>>> probabilistic reasoning will correct them. The key >>>>> point is >>>>> >>>>>>>>>>>>>>> that Alchemy >>>>> >>>>>>>>>>>>>>> doesn't have to learn from scratch, proving Wolpert >>>>> and >>>>> >>>>>>>>>>>>>>> Macready's no free >>>>> >>>>>>>>>>>>>>> lunch theorem wrong by performing well on a variety of >>>>> classes >>>>> >>>>>>>>>>>>>>> of problems, >>>>> >>>>>>>>>>>>>>> not just some. >>>>> >>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>> On Wednesday, August 3, 2016 at 4:01:15 PM UTC-3, >>>>> Kevin Liu >>>>> >>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>> wrote: >>>>> >>>>>>>>>>>>>>>> Hello Community, >>>>> >>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>> I'm in the last pages of Pedro Domingos' book, the >>>>> Master >>>>> >>>>>>>>>>>>>>>> Algo, one of two recommended by Bill Gates to learn >>>>> about AI. >>>>> >>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>> From the book, I understand all learners have to >>>>> represent, >>>>> >>>>>>>>>>>>>>>> evaluate, and optimize. There are many types of >>>>> learners that >>>>> >>>>>>>>>>>>>>>> do this. What >>>>> >>>>>>>>>>>>>>>> Domingos does is generalize these three parts, (1) >>>>> using >>>>> >>>>>>>>>>>>>>>> Markov Logic >>>>> >>>>>>>>>>>>>>>> Network to represent, (2) posterior probability to >>>>> evaluate, >>>>> >>>>>>>>>>>>>>>> and (3) >>>>> >>>>>>>>>>>>>>>> genetic search with gradient descent to optimize. The >>>>> >>>>>>>>>>>>>>>> posterior can be >>>>> >>>>>>>>>>>>>>>> replaced for another accuracy measure when it is >>>>> easier, as >>>>> >>>>>>>>>>>>>>>> genetic search >>>>> >>>>>>>>>>>>>>>> replaced by hill climbing. Where there are 15 popular >>>>> options >>>>> >>>>>>>>>>>>>>>> for >>>>> >>>>>>>>>>>>>>>> representing, evaluating, and optimizing, Domingos >>>>> >>>>>>>>>>>>>>>> generalized them into >>>>> >>>>>>>>>>>>>>>> three options. The idea is to have one unified >>>>> learner for >>>>> >>>>>>>>>>>>>>>> any application. >>>>> >>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>> There is code already done in R >>>>> >>>>>>>>>>>>>>>> https://alchemy.cs.washington.edu/. My question: >>>>> anybody in >>>>> >>>>>>>>>>>>>>>> the community vested in coding it into Julia? >>>>> >>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>> Thanks. Kevin >>>>> >>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>> On Friday, June 3, 2016 at 3:44:09 PM UTC-3, Kevin >>>>> Liu wrote: >>>>> >>>>>>>>>>>>>>>>> https://github.com/tbreloff/OnlineAI.jl/issues/5 >>>>> >>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>> On Friday, June 3, 2016 at 11:17:28 AM UTC-3, Kevin >>>>> Liu >>>>> >>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>> wrote: >>>>> >>>>>>>>>>>>>>>>>> I plan to write Julia for the rest of me life... >>>>> given it >>>>> >>>>>>>>>>>>>>>>>> remains suitable. I am still reading all of Colah's >>>>> >>>>>>>>>>>>>>>>>> material on nets. I ran >>>>> >>>>>>>>>>>>>>>>>> Mocha.jl a couple weeks ago and was very happy to >>>>> see it >>>>> >>>>>>>>>>>>>>>>>> work. Thanks for >>>>> >>>>>>>>>>>>>>>>>> jumping in and telling me about OnlineAI.jl, I will >>>>> look >>>>> >>>>>>>>>>>>>>>>>> into it once I am >>>>> >>>>>>>>>>>>>>>>>> ready. From a quick look, perhaps I could help and >>>>> learn by >>>>> >>>>>>>>>>>>>>>>>> building a very >>>>> >>>>>>>>>>>>>>>>>> clear documentation of it. Would really like to see >>>>> Julia a >>>>> >>>>>>>>>>>>>>>>>> leap ahead of >>>>> >>>>>>>>>>>>>>>>>> other languages, and plan to contribute heavily to >>>>> it, but >>>>> >>>>>>>>>>>>>>>>>> at the moment am >>>>> >>>>>>>>>>>>>>>>>> still getting introduced to CS, programming, and >>>>> nets at >>>>> >>>>>>>>>>>>>>>>>> the basic level. >>>>> >>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>> On Friday, June 3, 2016 at 10:48:15 AM UTC-3, Tom >>>>> Breloff >>>>> >>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>> wrote: >>>>> >>>>>>>>>>>>>>>>>>> Kevin: computers that program themselves is a >>>>> concept >>>>> >>>>>>>>>>>>>>>>>>> which is much closer to reality than most would >>>>> believe, >>>>> >>>>>>>>>>>>>>>>>>> but julia-users >>>>> >>>>>>>>>>>>>>>>>>> isn't really the best place for this speculation. >>>>> If >>>>> >>>>>>>>>>>>>>>>>>> you're actually >>>>> >>>>>>>>>>>>>>>>>>> interested in writing code, I'm happy to discuss >>>>> in >>>>> >>>>>>>>>>>>>>>>>>> OnlineAI.jl. I was >>>>> >>>>>>>>>>>>>>>>>>> thinking about how we might tackle code generation >>>>> using a >>>>> >>>>>>>>>>>>>>>>>>> neural framework >>>>> >>>>>>>>>>>>>>>>>>> I'm working on. >>>>> >>>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>>> On Friday, June 3, 2016, Kevin Liu < >>>>> [email protected]> >>>>> >>>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>>> wrote: >>>>> >>>>>>>>>>>>>>>>>>>> If Andrew Ng who cited Gates, and Gates who cited >>>>> >>>>>>>>>>>>>>>>>>>> Domingos (who did not lecture at Google with a >>>>> TensorFlow >>>>> >>>>>>>>>>>>>>>>>>>> question in the >>>>> >>>>>>>>>>>>>>>>>>>> end), were unsuccessful penny traders, Julia was >>>>> a >>>>> >>>>>>>>>>>>>>>>>>>> language for web design, >>>>> >>>>>>>>>>>>>>>>>>>> and the tribes in the video didn't actually solve >>>>> >>>>>>>>>>>>>>>>>>>> problems, perhaps this >>>>> >>>>>>>>>>>>>>>>>>>> would be a wildly off-topic, speculative >>>>> discussion. But >>>>> >>>>>>>>>>>>>>>>>>>> these statements >>>>> >>>>>>>>>>>>>>>>>>>> couldn't be farther from the truth. In fact, if I >>>>> had >>>>> >>>>>>>>>>>>>>>>>>>> known about this >>>>> >>>>>>>>>>>>>>>>>>>> video some months ago I would've understood >>>>> better on how >>>>> >>>>>>>>>>>>>>>>>>>> to solve a >>>>> >>>>>>>>>>>>>>>>>>>> problem I was working on. >>>>> >>>>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>>>> For the founders of Julia: I understand your >>>>> tribe is >>>>> >>>>>>>>>>>>>>>>>>>> mainly CS. This master algorithm, as you are >>>>> aware, would >>>>> >>>>>>>>>>>>>>>>>>>> require >>>>> >>>>>>>>>>>>>>>>>>>> collaboration with other tribes. Just citing the >>>>> obvious. >>>>> >>>>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>>>> On Friday, June 3, 2016 at 10:21:25 AM UTC-3, >>>>> Kevin Liu >>>>> >>>>>>>>>>>>>>>>>>>> >>>>> >>>>>>>>>>>>>>>>>>>> wrote: >>>>> >>>>>>>>>>>>>>>>>>>>> There could be parts missing as Domingos >>>>> mentions, but >>>>> >>>>>>>>>>>>>>>>>>>>> induction, backpropagation, genetic programming, >>>>> >>>>>>>>>>>>>>>>>>>>> probabilistic inference, >>>>> >>>>>>>>>>>>>>>>>>>>> and SVMs working together-- what's speculative >>>>> about the >>>>> >>>>>>>>>>>>>>>>>>>>> improv >>>> >>>>
