Towards Deep Developmental Learning

By Olivier Sigaud, Alain Droniou. 2016

47 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Representation & Self-Supervised Learning

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

1. Martial Hebert
2. Yu-Xiong Wang
3. Deva Ramanan
4. Zongben Xu
5. Jun Shu
6. Deyu Meng
7. Abhinav Kumar Gupta
8. Ross B. Girshick

In Control and Systems Engineering

1. Martial Hebert
2. Deva Ramanan
3. Jun Tani
4. Deyu Meng
5. Jung-Hun Hwang
6. James M. Rehg
7. Alireza Fathi

In Representation & Self-Supervised Learning

1. Martial Hebert
2. Deva Ramanan
3. Yu-Xiong Wang
4. Deyu Meng
5. Zongben Xu
6. Jun Shu
7. Jun Tani
8. Abhinav Kumar Gupta

Citations in the corpus

• Growing a Brain: Fine-Tuning by Increasing Model Capacity (2017, background): “In a broad sense, our approach is related to developmental learning [26, 16, 36] and lifelong learning [41, 25, 39, 29].”
• Seamless Integration and Coordination of Cognitive Skills in Humanoid Robots: A Deep Learning Approach (2017, background): “the PFC layer are equipped with recurrent connections which are essential to handle dynamic sequential data [1], [9], [39].”
• Small Sample Learning in Big Data Era (2018, background): “Recently, developmental learning (Sigaud and Droniou, 2016) and lifelong learning (Thrun and Mitchell, 1995; Mitchell et al.”