Speaker: Qiong Zhang, Assistant Professor, School of Mathematical and Statistical Sciences, Clemson University Title: A Brief Overview on Bayesian Optimization Abstract: In this talk, I will give a...
Speaker: Lulu Kang, associate professor of applied mathematics, Illinois Institute of Technology Description: We aim to design a fairness-aware allocation approach to maximize the geographical...
Speaker: Kinjal Basu, staff applied researcher LinkedIn Description: Key problems arising in web applications (with millions of users and thousands of items) can be formulated as Linear Programs (LP)...
Speaker: Yiou Li, assistant professor of statistics, DePaul University Description: Experimental designs for a generalized linear model (GLM) often depend on the specification of the model, including...
Speaker: Fred Hickernell, professor of mathematics, Illinois Institute of Technology Description: Quasi-Monte Carlo (QMC) methods achieve substantial efficiency gains by replacing independent and...
Speaker: Hadis Anahideh, Research Assistant Professor of Mechanical and Industrial Engineering, UIC Description: limited informative data remains the primary challenge for the optimization expensive...
Speaker: Jiuhai Chen, Ph.D. candidate (AMAT) Illinois Tech Description: In this work, we present a new particle-based VI methods for Bayesian inference, inspired by a discrete energetic variational...
Speaker: Jagadeeswaran Rathinavel, Illinois Tech Ph.D. candidate (AMAT) Description: Automatic cubatures approximate integrals to user-specified error tolerances. For high dimensional problems, it is...
Speaker: Romà Domènech Masana, Illinois Tech Ph.D. candidate (AMAT) Description: The idea focuses on making more complex splits. A Random Tree is grown by several steps. A Random Tree needs a dataset...
Speaker: Kan Zhang, Illinois Tech Ph.D. candidate (AMAT) Description: Computing the expected value of a parameter via Bayesian inference involves the numerical approximation of the quotient of two...
