On Certifying Non-Uniform Bounds against Adversarial Attacks
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In this paper, the authors present successful field test experience in the use of neural networks for short-term electrical load forecasting. After reviewing the importance of load forecasting as a key planning tool for a modern energy management system (E ...
The low er and upper bounds for the information capacity of two-layer feedforward neural networks with binary interconnections, integer thresholds for the hidden units, and zero threshold for the output unit is obtained through two steps, First, through a ...
We pursue a time-domain feedback analysis of adaptive schemes with nonlinear update relations. We consider commonly used algorithms in blind equalization and neural network training and study their performance in a purely deterministic framework. The deriv ...
The authors present the application of an artificial neural network, Kohonen's self-organizing feature map, for the classification of power system states. This classifier maps vectors of an N-dimensional space to a two-dimensional neural net in a no ...
Body accelerations during human walking are recorded by a portable measuring device. A new method for parameterising body accelerations is introduced. The parameters are presented to a Kohonen neural network classifier and the feasibility of identification ...
The operating point of a power system can be defined as a vector whose components are active and reactive power measurements. If the security criterion is prevention of line overloads, the boundaries of the secure domain of the state space are given by the ...
Neural networks are highly effective tools for pose estimation. However, robustness to outof-domain data remains a challenge, especially for small training sets that are common for real world applications. Here, we probe the generalization ability with thr ...
A non-intrusive reduced-basis (RB) method is proposed for parametrized unsteady flows. A set of reduced basis functions are extracted from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD), and the coefficients of the redu ...