Participant Information
Jim Lo from UMBC.
Paper: Are empirical covariance matrices what biological neural networks learn?
A computational model of biological neural networks will be presented to answer the above question. It is the only single computational model that answers eight long-standing holy-grail questions in neuroscience and is believed to be the common cortical algorithm long hypothesized. As a learning machine, it is the only one that performs "photographic learning", "real-time learning", and "maximal generalization". It is also the only multilayer network (with or without feedback connections) that is capable of unsupervised learning. The computational model provides a large number of research opportunities for understanding the brain, developing intelligent and cognitive machines, processing big data (including those in finance and insurance), and possibly helping find genetic causes of diseases.