Abstract: The most common machine learning algorithms operate on finite-dimensional vectorial feature representations. In many applications, however, the natural representation of the data consists of more complex objects, for example functions, distributions, and sets, rather than finite-dimensional vectors. In this …
Barnabas Poczos (CMU) Title: Distribution Regression and its Applications Read More »
Abstract: In this talk, I will present our joint measurement of cosmic infrared background (CIB) and CII line emission from large scales at redshift z=2.5 using an MCMC analysis of cross-correlations of the 3 high-frequency Planck bands with both SDSS-III …
Anthony Pullen (NYU) Title: Revealing CII Emission with LSS Cross-correlations Read More »
ABSTRACT: In this talk, I'd like to discuss the intertwining importance and connections of three principles of data science in the title in data-driven decisions. Making prediction as its central task and embracing computation as its core, machine learning has …
Abstract: The discovery of the Higgs boson has completed the set of particles predicted by the Standard Model (SM). It has been established by the CMS and ATLAS Collaborations at the Large Hadron Collider that the discovered boson is consistent …