Results 1 to 10 of about 147,655 (25)

Conclusive discrimination by $N$ sequential receivers between $r\geq2$ arbitrary quantum states [PDF]

Russ. J. Math. Phys. 30, 219 - 238 (2023), 2021
In the present article, we develop a general framework for the description of discrimination between $r\geq2$ quantum states by $N\geq1$ sequential receivers in the case where each receiver obtains a conclusive result. This type of discrimination constitutes an $N$-sequential extension of the minimum-error discrimination by one receiver.
arxiv   +1 more source

Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models [PDF]

arXiv, 2022
The proposed method, Discriminator Guidance, aims to improve sample generation of pre-trained diffusion models. The approach introduces a discriminator that gives explicit supervision to a denoising sample path whether it is realistic or not. Unlike GANs, our approach does not require joint training of score and discriminator networks.
arxiv  

Fairness Testing: Testing Software for Discrimination [PDF]

, 2017
This paper defines software fairness and discrimination and develops a testing-based method for measuring if and how much software discriminates, focusing on causality in discriminatory behavior. Evidence of software discrimination has been found in modern software systems that recommend criminal sentences, grant access to financial products, and ...
arxiv   +1 more source

Data Interpolants -- That's What Discriminators in Higher-order Gradient-regularized GANs Are [PDF]

arXiv, 2023
We consider the problem of optimizing the discriminator in generative adversarial networks (GANs) subject to higher-order gradient regularization. We show analytically, via the least-squares (LSGAN) and Wasserstein (WGAN) GAN variants, that the discriminator optimization problem is one of interpolation in $n$-dimensions.
arxiv  

The objective function equality property of infoGAN for two-layer network [PDF]

arXiv, 2023
Information Maximizing Generative Adversarial Network (infoGAN) can be understood as a minimax problem involving two networks: discriminators and generators with mutual information functions. The infoGAN incorporates various components, including latent variables, mutual information, and objective function.
arxiv  

Exposing the Probabilistic Causal Structure of Discrimination [PDF]

, 2015
Discrimination discovery from data is an important task aiming at identifying patterns of illegal and unethical discriminatory activities against protected-by-law groups, e.g., ethnic minorities. While any legally-valid proof of discrimination requires evidence of causality, the state-of-the-art methods are essentially correlation-based, albeit, as it ...
arxiv   +1 more source

Certified answers for ordered quantum discrimination problems [PDF]

Phys. Rev. A 100, 042331 (2019), 2019
We investigate the quantum state discrimination task for sets of linear independent pure states with an intrinsic ordering. This structured discrimination problems allow for a novel scheme that provides a certified level of error, that is, answers that never deviate from the true value more than a specified distance and hence a control of the desired ...
arxiv   +1 more source

Locally Valid and Discriminative Prediction Intervals for Deep Learning Models [PDF]

arXiv, 2021
Crucial for building trust in deep learning models for critical real-world applications is efficient and theoretically sound uncertainty quantification, a task that continues to be challenging. Useful uncertainty information is expected to have two key properties: It should be valid (guaranteeing coverage) and discriminative (more uncertain when the ...
arxiv  

FairNet: A Measurement Framework for Traffic Discrimination Detection on the Internet [PDF]

arXiv, 2021
Network neutrality is related to the non-discriminatory treatment of packets on the Internet. Any deliberate discrimination of traffic of one application while favoring others violates the principle of neutrality. Many countries have enforced laws against such discrimination.
arxiv  

Contextual advantage for state discrimination [PDF]

Phys. Rev. X 8, 011015 (2018), 2017
Finding quantitative aspects of quantum phenomena which cannot be explained by any classical model has foundational importance for understanding the boundary between classical and quantum theory. It also has practical significance for identifying information processing tasks for which those phenomena provide a quantum advantage.
arxiv   +1 more source