Results 11 to 20 of about 5,656,159 (367)
Noise: A Flaw in Human Judgment
Vikalpa The Journal for Decision Makers, 2023 This book is a deep, detailed dive into the science behind decision making. It focuses on how decisions and judgment are made, what influences them, and how better decisions can be made.
Gaurav Sood, A. Gelman, Christian Robert
semanticscholar +1 more source
International Journal of Modern Physics D, 2020 We show that when the gravitational field is treated quantum-mechanically, it induces fluctuations — noise — in the lengths of the arms of gravitational wave detectors. The characteristics of the noise depend on the quantum state of the gravitational field and can be calculated exactly in several interesting cases.
Parikh, M, Wilczek, Frank, Zahariade, G
openaire +6 more sources
Noise-induced barren plateaus in variational quantum algorithms [PDF]
Nature Communications, 2020 Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise on NISQ devices places fundamental limitations on VQA performance.
Samson Wang +6 more
semanticscholar +1 more source
SSRN Electronic Journal, 2014 We introduce noisy information in the determination of stock prices. Agents receive a noisy signal about the structural shock driving future dividend variations. The resulting equilibrium stock price includes a transitory component { the \noise bubble" { which can be responsible for boom and bust episodes unrelated to economic fundamentals.
Forni, Mario +3 more
openaire +8 more sources
Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach [PDF]
Computer Vision and Pattern Recognition, 2016 We present a theoretically grounded approach to train deep neural networks, including recurrent networks, subject to class-dependent label noise. We propose two procedures for loss correction that are agnostic to both application domain and network ...
Giorgio Patrini +4 more
semanticscholar +1 more source
2020 IEEE International Symposium on Information Theory (ISIT), 2020 We introduce Noise Recycling, a method that substantially enhances decoding performance of orthogonal channels subject to correlated noise without the need for joint encoding or decoding. The method can be used with any combination of codes, code-rates and decoding techniques.
Cohen, Alejandro +3 more
openaire +7 more sources
Calibrating Noise to Sensitivity in Private Data Analysis
Theory of Cryptography Conference, 2006 We continue a line of research initiated in [10, 11] on privacy-preserving statistical databases. Consider a trusted server that holds a database of sensitive information.
C. Dwork +3 more
semanticscholar +1 more source
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source