We propose a mini-batching scheme for improving the theoretical complexity and practical performance of semi-stochastic gradient descent applied to the problem of minimizing a str...
—In this work, we have developed tools to analyze prokaryotic cells growing in monolayers in a microfluidic device. Individual bacterial cells are identified using a novel curv...
—Coarse-graining (or granularization) of structures from transmission electron microscopy (EM volumes) has been shown to be useful for a variety of structural analysis applicatio...
—The tasks of online data reduction and outlier rejection are both of high interest when large amounts of data are to be processed for inference. Rather than performing these tas...
—Interest in deep probabilistic graphical models has increased in recent years, due to their state-of-the-art performance on many machine learning applications. Such models are t...
David E. Carlson, Ya-Ping Hsieh, Edo Collins, Lawr...
—While the quest of end users for fast and convenient Internet services grows steadily, energy-hungry data centers correspondingly expand in both numbers and scale - a fact that ...
Abstract—Microscopy imaging, including fluorescence microscopy and electron microscopy, has taken a prominent role in life science research and medicine due to its ability to in...
Abstract—One disadvantage of all fluorescence imaging modalities is a poor axial resolution. To overcome this issue, we propose a novel approach to reconstruct fluorescence vol...
Denis Fortun, Paul Guichard, Ning Chu, Michael Uns...
—We investigate the problem of online optimization under adversarial perturbations. In each round of this repeated game, a player selects an action from a decision set using a ra...
Mehmet A. Donmez, Maxim Raginsky, Andrew C. Singer
—We consider a compressive hyperspectral imaging reconstruction problem, where three-dimensional spatio-spectral information about a scene is sensed by a coded aperture snapshot ...
Jin Tan, Yanting Ma, Hoover F. Rueda, Dror Baron, ...