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 ...
This paper presents an improved adaptive algorithm for enhanced data hiding under HH-subband Haar Wavelet coefficients of a gray scale host image. The algorithm uses an optimal se...
Stuti Bazaj, Sachin Modi, Anand Mohan, S. P. Singh
The main theme of this paper is to develop a novel eigenvalue optimization framework for learning a Mahalanobis metric. Within this context, we introduce a novel metric learning a...
Abstract—This paper revisits the classical problem of multiquery optimization in the context of RDF/SPARQL. We show that the techniques developed for relational and semi-structur...
Wangchao Le, Anastasios Kementsietsidis, Songyun D...
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...