Published in March 2023
Authors
Z. Zou, K. Chen, Z. Shi, Y. Guo, and J. Ye
Abstract
Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Over the past…
Published in November 1998
Authors
Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner
Abstract
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can…
Published in September 2023
Authors
J. K. Eshraghian et al.
Abstract
The brain is the perfect place to look for inspiration to develop more efficient neural networks. The inner workings of our synapses and neurons provide a glimpse at what the future of…
Published in March 2021
Authors
W. Samek, G. Montavon, S. Lapuschkin, C. J. Anders, and K.-R. Müller
Abstract
With the broader and highly successful usage of machine learning (ML) in industry and the sciences, there has been a growing demand for explainable artificial…
Published in Jan 2021
Authors
F. Zhuang et al.
Abstract
Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains. In this way, the dependence on a…
Published in May 2021
Authors
B. Schölkopf, F. Locatello, S. Bauer, N. R. Ke, N. Kalchbrenner, A. Goyal, and Y. Bengio
Abstract
The two fields of machine learning and graphical causality arose and are developed separately. However, there is, now, cross-pollination…
PUBLISHED IN MARCH 2023
Title
Radar-Based Monitoring of Vital Signs
Authors
G. Paterniani et al.
Summary
Radar techniques aimed at health monitoring have been investigated recently and have gained sufficient interest as a potential technique for monitoring human vital signs. Radar technologies…
Authors
L. Ruff, J. R. Kauffmann, R. A. Vandermeulen, G. Montavon, W. Samek, M. Kloft, T. G. Dietterich, and K.-R. Müller
Abstract
Deep learning approaches to anomaly detection (AD) have recently improved the state of the art in detection performance on complex data…
Published in January 2016
Authors
B. Shahriari, K. Swersky, Z. Wang, R. P. Adams, and N. de Freitas
Abstract
Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems, and large-scale heterogeneous computing and…
Published in June 2022
Authors
M. Noor-A-Rahim, Z. Liu, H. Lee, M. O. Khyam, J. He, D. Pesch, K. Moessner, W. Saad, and H. V. Poor
Abstract
We are on the cusp of a new era of connected autonomous vehicles with…