Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence
By Daniel L. Silver. 2011
38 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Thang Van Doan
- Pierre Alquier
- Alexander Rainer Tassilo Gepperth
- Barbara Hammer
- Mehdi Abbana Bennani
- Bogdan Mazoure
- Guillaume Rabusseau
- Shan Suthaharan
In Computer Vision and Pattern Recognition
- Thang Van Doan
- Pierre Alquier
- Alexander Rainer Tassilo Gepperth
- Barbara Hammer
- Mehdi Abbana Bennani
- Bogdan Mazoure
- Guillaume Rabusseau
- Shan Suthaharan
Citations in the corpus
- A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix (2020, background): “Continual learning (CL) or lifelong learning [Thrun, 1995, Chen and Liu, 2018] has been one of the most important milestone on the path to building artificial general intelligence [Silver, 2011].”
- Big data classification: problems and challenges in network intrusion prediction with machine learning (2014, methodology): “One of the challenges, as stated in [19], is the scalability which is an important requirement for Big Data applications.”
- Incremental learning algorithms and applications (2016, background): “Lifelong learning, in contrast, refers to the situation of continuous model adaptation based on a constantly arriving data stream [38, 149].”