no code implementations • CVPR 2018 • Wenqi Wang, Yifan Sun, Brian Eriksson, Wenlin Wang, Vaneet Aggarwal
Deep neural networks have demonstrated state-of-the-art performance in a variety of real-world applications.
1 code implementation • 21 Dec 2017 • Dejiao Zhang, Yifan Sun, Brian Eriksson, Laura Balzano
Unsupervised clustering is one of the most fundamental challenges in machine learning.
no code implementations • 17 Mar 2017 • Urvashi Oswal, Swayambhoo Jain, Kevin S. Xu, Brian Eriksson
In this paper, we consider matrix approximation by sampling predefined \emph{blocks} of columns (or rows) from the matrix.
no code implementations • 24 Feb 2016 • Swayambhoo Jain, Urvashi Oswal, Kevin S. Xu, Brian Eriksson, Jarvis Haupt
The measurement and analysis of Electrodermal Activity (EDA) offers applications in diverse areas ranging from market research, to seizure detection, to human stress analysis.
no code implementations • 10 Jun 2014 • Zhaoshi Meng, Brian Eriksson, Alfred O. Hero III
Gaussian graphical models (GGM) have been widely used in many high-dimensional applications ranging from biological and financial data to recommender systems.
no code implementations • 20 Mar 2014 • Branislav Kveton, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson
The objective in these problems is to learn how to maximize a modular function on a matroid.
no code implementations • NeurIPS 2013 • Victor Gabillon, Branislav Kveton, Zheng Wen, Brian Eriksson, S. Muthukrishnan
Maximization of submodular functions has wide applications in machine learning and artificial intelligence.