Concept

Perceptron

Publications associées (219)

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Improved Similarity Measures for Small Sets of Spike Trains

Wulfram Gerstner, Richard Naud, Joao Emanuel Felipe Gerhard, Skander Mensi

Multiple types of measures have been developed to measure the similarity between two spike trains. These were extensively used to classify neuron responses according to stimuli and to validate mathematical models that predict the spike times. Here we analy ...

2010

On Joint Modelling of Grapheme and Phoneme Information using KL-HMM for ASR

Hervé Bourlard, Guillermo Aradilla

In this paper, we propose a simple approach to jointly model both grapheme and phoneme information using Kullback-Leibler divergence based HMM (KL-HMM) system. More specifically, graphemes are used as subword units and phoneme posterior probabilities estim ...

Idiap2009

Application of Artificial Neural Network to Predict Survival Time for Patients with Bladder Cancer

Rafal Tomasz Dlugosz

This paper presents an application of an artificial neural network to determine survival time of patients with a bladder cancer. Different learning methods have been investigated to find a solution, which is most optimal from a computational complexity poi ...

Springer-Verlag2009

Convex Variational Bayesian Inference for Large Scale Generalized Linear Models

Matthias Seeger

We show how variational Bayesian inference can be implemented for very large binary classification generalized linear models. Our relaxation is shown to be a convex problem for any log-concave model, and we provide an efficient double loop algorithm for so ...

2009

MLP Based Hierarchical System for Task Adaptation in ASR

Hervé Bourlard, Joel Praveen Pinto

We investigate a multilayer perceptron (MLP) based hierarchical approach for task adaptation in automatic speech recognition. The system consists of two MLP classifiers in tandem. A well-trained MLP available off-the-shelf is used at the first stage of the ...

2009

Improved Phone Posterior Estimation Through k-NN and MLP-Based Similarity

Benjamin Picart

In this work, we investigate the possible use of k-nearest neighbour (kNN) classifiers to perform frame-based acoustic phonetic classification, hence replacing Gaussian Mixture Models (GMM) or MultiLayer Perceptrons (MLP) used in standard Hidden Markov Mod ...

Idiap2009

A Large Margin Algorithm for Forced Alignment

We describe and analyze a discriminative algorithm for learning to align a phoneme sequence of a speech utterance with its acoustical signal counterpart by predicting a timing sequence representing the phoneme start times. In contrast to common HMM-based a ...

John Wiley and Sons2009

Purely URL-based Topic Classification

Monika Henzinger, Ingmar Weber, Eda Baykan, Ludmila Marian

Given only the URL of a web page, can we identify its topic? This is the question that we examine in this paper. Usually, web pages are classified using their content, but a URL-only classifier is preferable, (i) when speed is crucial, (ii) to enable conte ...

2009

The Projectron: a Bounded Kernel-Based Perceptron

Barbara Caputo

We present a discriminative online algorithm with a bounded memory growth, which is based on the kernel-based Perceptron. Generally, the required memory of the kernel-based Perceptron for storing the online hypothesis is not bounded. Previous work has been ...

2008

The Projectron: a Bounded Kernel-Based Perceptron

Barbara Caputo

IDIAP2008