Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.
Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.
Golubtsov P., , in: Advances in Intelligent Systems and Computing book series Vol. 1127. Advances in Intelligent Systems, Computer Science and Digital EconomicsVol. 1127: Advances in Intelligent Systems, Computer Science and Digital Economics.: Switzerland: Springer, 2020. P. 274–298.
Procedures of sequential updating of information are important for “big data streams” processing because they avoid accumulating and storing large data sets. As a model of information accumulation, we study the Bayesian updating procedure for linear experiments. Analysis and gradual transformation of the original processing scheme in order to increase its efficiency lead to certain ...