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Detection of Bad PMU Data using Machine Learning Techniques

Publications associées (38)

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The committee machine: Computational to statistical gaps in learning a two-layers neural network

Nicolas Macris, Florent Gérard Krzakala, Lenka Zdeborová, Jean François Emmanuel Barbier

Heuristic tools from statistical physics have been used in the past to locate the phase transitions and compute the optimal learning and generalization errors in the teacher-student scenario in multi-layer neural networks. In this contribution, we provide ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Nonbinary Associative Memory With Exponential Pattern Retrieval Capacity and Iterative Learning

Mohammad Amin Shokrollahi, Krishna Kumar, Amir Hesam Salavati

We consider the problem of neural association for a network of nonbinary neurons. Here, the task is to first memorize a set of patterns using a network of neurons whose states assume values from a finite number of integer levels. Later, the same network sh ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Estimating Beauty Ratings of Videos using Supervoxels

Sabine Süsstrunk, Appu Shaji, Gökhan Yildirim

The major low-level perceptual components that influence the beauty ratings of video are color, contrast, and motion. To estimate the beauty ratings of the NHK dataset, we propose to extract these features based on supervoxels, which are a group of pixels ...

2013

Definitive Consensus for Distributed Data Inference

Leonidas Georgopoulos

Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...

EPFL2011

Information Processing and Structure of Dynamical Networks

Ali Ajdari Rad

Networks are everywhere and we are confronted with many networks in our daily life. Networks such as Internet, World Wide Web, social, biological and economical networks have been subject to extensive studies in the last decade. The volume of publications ...

EPFL2011

PyBrain

Yi Sun, Daniël Pieter Wierstra, Tom Schaul

PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined environments and benchmarks to test and compare algorithms. ...

Massachusetts Institute of Technology Press2010

A recurrent model for perceptual learning

Michael Herzog

Perceptual learning has received enhanced interest during the last years both from theoreticians and experimentalists. Recent experimental results reveal that mechanisms underlying perceptual learning are more complex than previously expected, thereby ruli ...

Optical Society of America1999

A feedback analysis of perceptron learning for neural networks

Ali H. Sayed

This paper provides a time-domain feedback analysis of the perceptron learning algorithm. It studies the robustness performance of the algorithm in the presence of uncertainties that might be due to noisy perturbations in the reference signal or to modelin ...

1995