activity
20172021
most citedDeep Unsupervised Clustering Using Mixture of Autoencoders

37 citations · 73 across the 5 of their papers we have counts for

collaborators

9 papers

math.OC20211 cited

Certainty Equivalent Quadratic Control for Markov Jump Systems

Zhe Du, Yahya Sattar, Davoud Ataee Tarzanagh +3

Real-world control applications often involve complex dynamics subject to abrupt changes or variations. Markov jump linear systems (MJS) provide a rich framework for modeling such…

stat.ML2020

Preference Modeling with Context-Dependent Salient Features

Amanda Bower, Laura Balzano

We consider the problem of estimating a ranking on a set of items from noisy pairwise comparisons given item features. We address the fact that pairwise comparison data often refle…

cs.LG2019

Online matrix factorization for Markovian data and applications to Network Dictionary Learning

Hanbaek Lyu, Deanna Needell, Laura Balzano

Online Matrix Factorization (OMF) is a fundamental tool for dictionary learning problems, giving an approximate representation of complex data sets in terms of a reduced number of…

eess.SY20191 cited

Mode Clustering for Markov Jump Systems

Zhe Du, Necmiye Ozay, Laura Balzano

In this work, we consider the problem of mode clustering in Markov jump models. This model class consists of multiple dynamical modes with a switching sequence that determines how…

math.OC20192 cited

A Memory-efficient Algorithm for Large-scale Sparsity Regularized Image Reconstruction

Greg Ongie, Naveen Murthy, Laura Balzano +1

We derive a memory-efficient first-order variable splitting algorithm for convex image reconstruction problems with non-smooth regularization terms. The algorithm is based on a pri…

stat.ML2018

Streaming PCA and Subspace Tracking: The Missing Data Case

Laura Balzano, Yuejie Chi, Yue M. Lu

For many modern applications in science and engineering, data are collected in a streaming fashion carrying time-varying information, and practitioners need to process them with a…