Machine learning is playing a central role in the digital revolution,
in which massive and never-ending data is collected from various
sources such as online commerce, social networking, and online
collaboration. This large amount of data is often noisy or partial.
In this talk I will present learning algorithms appropriate for this
new era: algorithms that not only can handle massive amounts of data
but can also leverage large data sets to reduce the required runtime;
and algorithms that can use the multitude of examples to compensate
for lack of full information on each individual example.