We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
We study the design and approximation of optimal crowdsourcing contests. Crowdsourcing contests can be modeled as all-pay auctions because entrants must exert effort up-front to e...
Shuchi Chawla, Jason D. Hartline, Balasubramanian ...
We have developed methods for segmentation and tracking of cells in time-lapse phase-contrast microscopy images. Our multi-object Bayesian algorithm detects and tracks large num...
David House, Matthew Walker, Zheng Wu, Joyce Wong,...
This paper presents a method to quantitatively evaluate
information contributions of individual bottom-up and topdown
computing processes in object recognition. Our objective
is...
We study the problem of estimating the illuminant's direction from images of textured surfaces. Given an isotropic, Gaussian random surface with constant albedo, Koenderink an...