I roughly read this paper. I don't think I fully understand, but I guess it is a start. Machine learning seems to be a vast field...😵💫
RT @omaclaren: @koyuli_public Think this might count? https://t.co/l2JtgjTW4e
@koyuli_public Think this might count? https://t.co/l2JtgjTW4e
@cubic_logic @learnfromerror @NeuroStats @richarddmorey You could perhaps talk about the ‘capacity’ or VC dimension of a set of models a la Vapnik, I guess. But while perhaps useful as an intuitive guide, I don’t think these things really solve real philos
Very interesting paper on the relation between Popper's notion of falsification and statistical learning theory, and the (supposed) differences between scientific learning and machine learning: https://t.co/B9WW9AUsYM
@Collinsjo12 @learnfromerror @HardyHulley @polanalysis Yeah there’s a lot of similar ideas around. No one has really fully succeeded imo. Vapnik made an interesting attempt to relate his work involving complexity class trade offs to Popper’s work - https:/
I just noticed that this was written by this David Corfield! https://t.co/eBLsQZd2ES
I'm reading this on #springerlink https://t.co/FAFZLoDTUD
RT @GeorgeShiber: #Falsificationism and #Statistical-Learning-Theory: Comparing the #Popper and VCT Dimensions https://t.co/nkfIPs62Uk #Phi…
RT @GeorgeShiber: #Falsificationism and #Statistical-Learning-Theory: Comparing the #Popper and VCT Dimensions https://t.co/nkfIPs62Uk #Phi…
RT @GeorgeShiber: #Falsificationism and #Statistical-Learning-Theory: Comparing the #Popper and VCT Dimensions https://t.co/nkfIPs62Uk #Phi…
RT @GeorgeShiber: #Falsificationism and #Statistical-Learning-Theory: Comparing the #Popper and VCT Dimensions https://t.co/nkfIPs62Uk #Phi…
#Falsificationism and #Statistical-Learning-Theory: Comparing the #Popper and VCT Dimensions https://t.co/nkfIPs62Uk #Philosophy of #Science