Learning low-degree functions on the discrete hypercube


题目:Learning low-degree functions on the discrete hypercube

报告人Alexandros EskenazisCentre national de la recherche scientifique, CNRS



Zoom会议:会议号:882 8540 7533,会议密码:028422



摘要:Let f be an unknown function on the n-dimensional discrete hypercube. How many values of f do we need in order to approximately reconstruct the function? In this talk, we shall discuss the random query model for this fundamental problem from computational learning theory. We will explain a newly discovered connection with a family of polynomial inequalities going back to Littlewood (1930) which will in turn allow us to derive sharper estimates for the query complexity of this model, exponentially improving those which follow from the classical Low-Degree Algorithm of Linial, Mansour and Nisan (1989), while maintaining a running time of the same order. Time permitting, we will also show a matching information-theoretic lower bound. Based on joint works with Paata Ivanisvili (UC Irvine) and Lauritz Streck (Cambridge).




Copyright (C)2023 哈尔滨工业大学数学研究院版权所有
电话:86413107      邮箱:IASM@hit.edu.cn