Keynote Talk: Model Based Machine Learning

The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.

The third edition of Academic Research Summit was held at the International Institute of Information Technology (IIIT) Hyderabad on the 24th and 25th of January 2018.

The agenda included keynotes and talks from distinguished researchers from India and across the world. The summit also had sessions focused on specific topics related to the theme of Artificial Intelligence: A Future with AI.

[imrannaseem]

At 9:08 he compares a simple problem (electrical current prediction given a certain voltage) with a much complicated problem of image recognition. IMHO to differentiate between computationally and statistically big data the targeted problem should be the same. So for instance the plane recognition problem, thousands of pictures of the similar type of aeroplane are computationally large but statistically insufficient. However may be a reduced number of pictures of various models may suffice statistically.

[AhmedIsam]

32:33 He said it the wrong way, actually the red is better than green and that's why it is amazing.

[alexanderkarpenko]

Unexpected to hear that SVM is a "funny approach for machine learning " (14:03 min). Vladimir Vapnik made an exceptional contribution to the development of the statistical learning theory, and I believe Professor Bishop did not mean what he said.

[jacobdavidcunningham]

1:30 If anybody wants this super long list lol

generative adversarial network
Markov random field
K-means clustering
Radial basis functions
decision trees
logistic regression
Kalman filter
kernel PCA
random forest
deep networks
principal components
Hidden Markov model
convolutional networks
support vector machines
Gaussian mixture
linear regression
independent component analysis
Gaussian process
factor analysis
Boltzmann machines

[Moha.ilcac_]

“Without much further ado” why the poor introduction to such an amazing lecture???

[KristoferPettersson]

You say that the model of a person restricts the expressions of freedom so that less data is needed to conclude that any data is a person - fine. But then you say that a convolutional layer represent a model of a person when it clearly is not. Rather the convolutional layer has parameters which iteratively change according to an algorithm to converge towards to a structured representation of a person. Clearly the product is the model we're after and the convolutional layer is more like a 'meta model'. It seems reasonable that the more degrees of freedom this meta model allows for the more kinds of models it can derive, right?

[bvdtrading]

Why he is holding water for the whole talk ? lol