[ISS4E] Fwd: November 24 Talk with SIGKDD Innovation Award Winner Pedro Domingos: "The Five Tribes of Machine Learning..."

S. Keshav keshav at uwaterloo.ca
Fri Nov 6 15:11:08 EST 2015


This may be of wide interest

thanks
keshav


Forwarded message:

> From: ACM Learning Center <learning at HQ.ACM.ORG>
> To: ACM-WEBINAR at LISTSERV.ACM.ORG
> Subject: November 24 Talk with SIGKDD Innovation Award Winner Pedro 
> Domingos: "The Five Tribes of Machine Learning..."
> Date: Thu, 5 Nov 2015 15:07:13 -0500
>
> --------------------------------------------------------------------------------
>
> November 24 Talk with SIGKDD Innovation Award Winner Pedro Domingos: 
> "The Five Tribes of Machine Learning..."
>
> --------------------------------------------------------------------------------
>
> Register TODAY 
> (http://event.on24.com/wcc/r/1087879/DDB691DE07A8B2C54CCDC9CECDB98D3F) 
> for the next free ACM Learning Webinar, "The Five Tribes of Machine 
> Learning (And What You Can Learn from Each)," presented on Thursday, 
> November 24, 2015 at 12 pm ET (11 am CT/10 am MT/9 am PT/5 pm GMT) by 
> Pedro Domingos, Professor of Computer Science at the University of 
> Washington in Seattle and winner of the SIGKDD Innovation. Gregory 
> Piatetsky-Shapiro, President of KDnuggets, founder of Knowledge 
> Discovery in Database (KDD) conferences, and co-founder of ACM SIGKDD, 
> moderates.
>
> (If you'd like to attend but can't make it to the virtual event, you 
> still need to register to receive a recording of the webinar when it 
> becomes available.)
>
> Note: You can stream this and all ACM Learning Webinars on your mobile 
> device, including smartphones and tablets.
>
> There are five main schools of thought in machine learning, and each 
> has its own master algorithm – a general-purpose learner that can in 
> principle be applied to any domain. The symbolists have inverse 
> deduction, the connectionists have backpropagation, the evolutionaries 
> have genetic programming, the Bayesians have probabilistic inference, 
> and the analogizers have support vector machines. What we really need, 
> however, is a single algorithm combining the key features of all of 
> them. In this webinar Pedro Domingos will summarize the five paradigms 
> and describe his work toward unifying them, including in particular 
> Markov logic networks. Pedro will conclude by speculating on the new 
> applications that a universal learner will enable, and how society 
> will change as a result.
>
> Duration: 60 minutes (including audience Q&A)
>
> Presenter:
> Pedro Domingos, University of Washington in Seattle; SIGKDD Innovation 
> Award Winner
> Pedro Domingos is a professor of computer science at the University of 
> Washington in Seattle. He is a winner of the SIGKDD Innovation Award, 
> the highest honor in data science. He is a Fellow of the Association 
> for the Advancement of Artificial Intelligence, and has received a 
> Fulbright Scholarship, a Sloan Fellowship, the National Science 
> Foundation’s CAREER Award, and numerous best paper awards. He 
> received his Ph.D. from the University of California at Irvine and is 
> the author or co-author of over 200 technical publications. He has 
> held visiting positions at Stanford, Carnegie Mellon, and MIT. He 
> co-founded the International Machine Learning Society in 2001. His 
> research spans a wide variety of topics in machine learning, 
> artificial intelligence, and data science, including scaling learning 
> algorithms to big data, maximizing word of mouth in social networks, 
> unifying logic and probability, and deep learning.
>
> Moderator:
> Gregory Piatetsky-Shapiro, KDnuggets; SIGKDD Co-Founder
> Gregory Piatetsky-Shapiro is President of KDnuggets, which provides 
> consulting in the areas of business analytics, data mining, data 
> science, and knowledge discovery. Previously, he led data mining and 
> consulting groups at GTE Laboratories, Knowledge Stream Partners, and 
> Xchange. Gregory is also Editor and Publisher of KDnuggets News and 
> the KDnuggets.com website, leading resources for data mining and 
> analytics news, software, jobs, courses, data, education, and more. 
> Gregory is the founder of Knowledge Discovery in Database (KDD) 
> conferences. In 1998, he co-founded ACM SIGKDD, the leading 
> professional organization for Knowledge Discovery and Data Mining, and 
> served in the roles of Director as well as Chair. Gregory has over 60 
> publications, with over 10,000 citations, including two best-selling 
> books and several edited collections on topics related to data mining 
> and knowledge discovery. Gregory was the first recipient of ACM SIGKDD 
> Service Award (2000). He also received the IEEE ICDM Outstanding 
> Service Award (2007) for contributions to data mining field and 
> community.
>
> Click 
> http://event.on24.com/wcc/r/1087879/DDB691DE07A8B2C54CCDC9CECDB98D3F 
> to register for this free webinar and be sure to share this with 
> friends and colleagues who may be interested in this topic. And check 
> out our past events, all available on demand 
> (http://learning.acm.org/webinar/).
>
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