no code implementations • 12 Dec 2022 • Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso
Hawkes processes have recently risen to the forefront of tools when it comes to modeling and generating sequential events data.
no code implementations • 19 May 2017 • Renbo Zhao, William B. Haskell, Jiashi Feng
We propose a unified framework to speed up the existing stochastic matrix factorization (SMF) algorithms via variance reduction.
no code implementations • 1 Apr 2017 • Renbo Zhao, William B. Haskell, Vincent Y. F. Tan
We revisit the stochastic limited-memory BFGS (L-BFGS) algorithm.
no code implementations • 4 Sep 2016 • Renbo Zhao, Vincent Y. F. Tan
The multiplicative update (MU) algorithm has been extensively used to estimate the basis and coefficient matrices in nonnegative matrix factorization (NMF) problems under a wide range of divergences and regularizers.
no code implementations • 30 Jul 2016 • Renbo Zhao, Vincent Y. F. Tan, Huan Xu
We develop a unified and systematic framework for performing online nonnegative matrix factorization under a wide variety of important divergences.
no code implementations • 10 Apr 2016 • Renbo Zhao, Vincent Y. F. Tan
We propose a unified and systematic framework for performing online nonnegative matrix factorization in the presence of outliers.
no code implementations • 15 Feb 2016 • Changho Suh, Vincent Y. F. Tan, Renbo Zhao
We study the top-$K$ ranking problem where the goal is to recover the set of top-$K$ ranked items out of a large collection of items based on partially revealed preferences.