A new algorithm for digital watermarking of largescale digital images is proposed in the article. The proposed algorithm provides watermark robustness to a wide range of host imag...
Nikolay Ivanovich Glumov, Vitaly Anatolyevich Mite...
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast mo...
Copy-move tampering is a common type of image synthesizing, where a part of an image is copied and pasted to another place to add or remove an object. In this paper, an efficient ...
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available ...
Network services play an important role in the Internet today. They serve as data caches for websites, servers for multiplayer games and relay nodes for Voice over IP (VoIP) conver...