10 citations · 28 across the 10 of their papers we have counts for
10 papers
Adversarially robust clustering with optimality guarantees
Soham Jana, Kun Yang, Sanjeev Kulkarni
We consider the problem of clustering data points coming from sub-Gaussian mixtures. Existing methods that provably achieve the optimal mislabeling error, such as the Lloyd algorit…
End-to-End Jet Classification of Boosted Top Quarks with the CMS Open Data
Michael Andrews, Bjorn Burkle, Yi-fan Chen +10
We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a…
Tensor Processing Units for Financial Monte Carlo
Francois Belletti, Davis King, Kun Yang +4
Monte Carlo methods are critical to many routines in quantitative finance such as derivatives pricing, hedging and risk metrics. Unfortunately, Monte Carlo methods are very computa…
High Performance Monte Carlo Simulation of Ising Model on TPU Clusters
Kun Yang, Yi-Fan Chen, Georgios Roumpos +2
Large-scale deep learning benefits from an emerging class of AI accelerators. Some of these accelerators' designs are general enough for compute-intensive applications beyond AI an…
Density Estimation via Discrepancy
Kun Yang, Hao Su, Wing Hung Wang
Given i.i.d samples from some unknown continuous density on hyper-rectangle , we attempt to learn a piecewise constant function that approximates this underlying density…
co-BPM: a Bayesian Model for Divergence Estimation
Kun Yang, Hao Su, Wing Hung Wong
Divergence is not only an important mathematical concept in information theory, but also applied to machine learning problems such as low-dimensional embedding, manifold learning,…