Concept

Nonlinear dimensionality reduction

Publications associées (497)

INTRA-CLASS COVARIANCE ADAPTATION IN PLDA BACK-ENDS FOR SPEAKER VERIFICATION

Multi-session training conditions are becoming increasingly common in recent benchmark datasets for both text-independent and text-dependent speaker verification. In the state-of-the-art i-vector framework for speaker verification, such conditions are addr ...

Ieee2017

Efﬁcient Feature Embeddings for Student Classiﬁcation with Variational Auto-encoders

Gathering labeled data in educational data mining (EDM) is a time and cost intensive task. However, the amount of available training data directly influences the quality of predictive models. Unlabeled data, on the other hand, is readily available in high ...

EDM2017

Subspace Regularized Dynamic Time Warping for Spoken Query Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

Deep neural network posterior probabilities are the best features for query detection in speech archives. Dynamic time warping (DTW) is the state-of-the-art solution for this task. Posterior features live in low-dimensional subspaces whereas, the current D ...

2017

Randomized Projections for Improved Sensing and Imaging in Positron Emission Tomography

Positron Emission Tomography (PET) aims at recovering the metabolic activity of an organ of interest. Established algorithms implemented in contemporary PET scans are based on an approximation of the inverse Radon transform, resulting in a suboptimal estim ...

2017

High-Order Accurate Adaptive Kernel Compression Time-Stepping Schemes for Fractional Differential Equations

Jan Sickmann Hesthaven, Daniel Henri Baffet

High-order adaptive methods for fractional differential equations are proposed. The methods rely on a kernel reduction method for the approximation and localization of the history term. To avoid complications typical to multistep methods, we focus our stud ...

Springer Verlag2017

Near-optimal Deployment of Dataflow Applications on Many-core Platforms with Real-time Guarantees

Alena Simalatsar, Stefanos Skalistis

Safe and optimal deployment of data-streaming applications on many-core platforms requires the realistic estimation of task Worst-Case Execution Time (WCET). On the other hand, task WCET depends on the deployment solution, due to the varying number of inte ...

IEEE2017

Fast Robust PCA on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

Ieee-Inst Electrical Electronics Engineers Inc2016

PCA using graph total variation

Pierre Vandergheynst, Nathanaël Perraudin, Benjamin Ricaud, Nauman Shahid, Vasilis Kalofolias

Mining useful clusters from high dimensional data has received sig- nificant attention of the signal processing and machine learning com- munity in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome th ...

Ieee2016

Low-Rank Matrices on Graphs: Generalized Recovery & Applications

Pierre Vandergheynst, Nathanaël Perraudin, Nauman Shahid

Many real world datasets subsume a linear or non-linear low-rank structure in a very low-dimensional space. Unfortunately, one often has very little or no information about the geometry of the space, resulting in a highly under-determined recovery problem. ...

2016

MATHICSE Technical Report : Spectral based discontinuous Galerkin reduced basis element method for parametrized Stokes problems

Alfio Quarteroni, Paolo Pacciarini

In this work we extend to the Stokes problem the Discontinuous Galerkin Reduced Basis Element (DGRBE) method introduced in [1]. By this method we aim at reducing the computational cost for the approximation of a parametrized Stokes problem on a domain part ...

MATHICSE2016

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search