We introduce a high-performance fingerprint liveness feature extraction technique that secured first place in LivDet 2023 Fingerprint Representation Challenge.
We introduce a distortion measure for images, Wasserstein distortion, that simultaneously generalizes pixel-level fidelity on the one hand and realism on the other.
Online advertisements are important elements in e-commerce sites, social media platforms, and search engines.
However, such a cooperative game may incur the degeneration problem where the predictor overfits to the uninformative pieces generated by a not yet well-trained generator and in turn, leads the generator to converge to a sub-optimal model that tends to select senseless pieces.
Rationalization is to employ a generator and a predictor to construct a self-explaining NLP model in which the generator selects a subset of human-intelligible pieces of the input text to the following predictor.
Simulation results illustrate that a distributed planning model is more sensitive to individual load differences, which is precisely the defect of the joint planning model.
This provides a valuable opportunity to develop a universal solution for debiasing, e. g., by learning the debiasing parameters from data.
We find modular tensor categories that realize candidate modular data constructed from Seifert fibered spaces and torus bundles over the circle that reveal many subtleties in the program.
Quantum Algebra Mathematical Physics Geometric Topology Mathematical Physics Quantum Physics 18M20, 57K16, 58J28
Online display advertising is growing rapidly in recent years thanks to the automation of the ad buying process.
In this paper, we study how to make use of decentralized datasets for training a robust scene text recognizer while keeping them stay on local devices.