Active Learning

author: Sanjoy Dasgupta, Department of Computer Science and Engineering, UC San Diego
author: John Langford, Microsoft Research
published: Aug. 26, 2009,   recorded: June 2009,   views: 50235


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Active learning is defined by contrast to the passive model of supervised learning where all the labels for learning are obtained without reference to the learning algorithm, while in active learning the learner interactively chooses which data points to label. The hope of active learning is that interaction can substantially reduce the number of labels required, making solving problems via machine learning more practical. This hope is known to be valid in certain special cases, both empirically and theoretically.

Variants of active learning have been investigated over several decades and fields. The focus of this tutorial is on general techniques which are applicable to many problems. At a mathematical level, this corresponds to approaches with provable guarantees under weakest-possible assumptions since real problems are more likely to fit algorithms which work under weak assumptions.

We believe this tutorial should be of broad interest. People working on or using supervised learning are often confronted with the need for more labels, where active learning can help. Similarly, in reinforcement learning, generalizing while interacting in more complex ways is an active research topic. Please join us.

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Download slides icon Download slides: icml09_dasgupta_langford_actl.pdf (454.2┬áKB)

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Reviews and comments:

Comment1 Javier, June 11, 2010 at 1:01 p.m.:

Where is the second part of this tutorial?

Comment2 Vijay Bhaskar Semwal, June 30, 2015 at 7:21 p.m.:

Best lecture ever

Comment3 Nick, March 29, 2017 at 3:23 p.m.:

I must implement a equivalence query in the active learning scenario, in a approximate way: using SVM or Recurrent Neural Network. My Oracle can answer to membership query. Is there litterature about? I can't find

Comment4 Kash, November 22, 2019 at 10:26 a.m.:

Learning from any source can help you to understand these things and it will help you to grow in a field. The share some good sources which you can use for learning and also join any course as well.

Comment7 Danny, June 10, 2020 at 4:28 p.m.:

Great discussion, so helpful! Thanks |

Comment8 Kerty, June 10, 2020 at 4:30 p.m.:

Another complex and brilliant discussion! Thank you

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Comment10 Ronald, March 10, 2023 at 4:29 p.m.:

Very wonderful article i must follow your page. thanks for sharing

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