ÃÛÌÇÖ±²¥

Bernd Krauskopf and Hinka OsingaDepartment of Mathematics, University of AucklandHetero-dimensional Cycles and BlendersRecent theoretical work on partially hyperbolic systems by Bonatti and Diaz (and others) has shown that chaotic dynamics may occur

Yury MakarychevToyota Technological Institute at Chicago (TTIC)Performance of Johnson-Lindenstrauss Transform for k-Means and k-Medians Clustering Consider an instance of Euclidean k-means or k-medians clustering. We show that the cost of the

Erin Ellefsen Department of Applied Mathematics University of ÃÛÌÇÖ±²¥ BoulderEfficiently finding steady states of nonlocal territorial models in EcologyThere are certain populations of animals that tend to move in social groups. We

Rebecca MorrisonDepartment of Computer Science, University of ÃÛÌÇÖ±²¥ BoulderRepresenting model error in reduced models of interacting systemsIn many applications of interacting systems, we are only interested in the dynamic behavior of a subset of

Catherine SulemDepartment of Mathematics, University of TorontoBloch theory and spectral gaps for linearized water wavesWe consider the movement of a free surface of a two-dimensional fluid over a variable bottom. We assume that the bottom has

Zhishen HuangDepartment of Applied Mathematics, University of ÃÛÌÇÖ±²¥ BoulderFinding local minimizers in nonconvex and non-smooth optimization We consider the problem of finding local minimizers in nonconvex and non-smooth optimization. The

John HarlimDepartments of Mathematics and Meteorology, Penn State UniversityManifold learning based computational methodsRecent success of machine learning has drawn tremendous interests in applied mathematics and scientific computations. In this

Brett WernerDepartment of Mathematics, University of ÃÛÌÇÖ±²¥ BoulderOn Machine LearningMachine learning (ML) is the process of making computers learn without specifically programming them to do so. ML has a variety of applications including

Ashutosh TrivediDepartment of Computer Science, University of ÃÛÌÇÖ±²¥ BoulderReinforcement Learning and Formal RequirementsReinforcement learning is an approach to controller synthesis where agents rely on reward signals to choose actions in order

Osita OnyejekweDepartment of Mathematics, University of ÃÛÌÇÖ±²¥ BoulderFeature Detection in Observed Climate FactorsThe detection of inflection points is an important task in science and engineering. This task is onerous with subjective results.