Publications related to Augmented Lagrangian Methods for Provable and Scalable Machine Learning

An optimal first-order solver for the TV-$L_1$ optical flow problem

Pierre Vandergheynst, Gilles Puy, Emmanuel D'Angelo

In this study, we address the problem of computing efficiently a dense optical flow between two images under a total variation (TV) regularization and an

L_1

norm data fidelity constraint using a variational method. We build upon Nesterov's framework for ...

2010

An Adaptive Initialization Method for Speaker Diarization based on Prosodic Features

David Imseng

The following article presents a novel, adaptive initialization scheme that can be applied to most state-ofthe-art Speaker Diarization algorithms, i.e. algorithms that use agglomerative hierarchical clustering with Bayesian Information Criterion (BIC) and ...

2010

An Adaptive Initialization Method for Speaker Diarization based on Prosodic Features

David Imseng

The following article presents a novel, adaptive initialization scheme that can be applied to most state-ofthe-art Speaker Diarization algorithms, i.e. algorithms that use agglomerative hierarchical clustering with Bayesian Information Criterion (BIC) and ...

Idiap2010

Maximizing the net present value of a project under uncertainty

Daniel Kuhn, Wolfram Wiesemann

We address the maximization of a project’s expected net present value when the activity durations and cash flows are described by a discrete set of alternative scenarios with associated occurrence probabilities. In this setting, the choice of scenario-inde ...

Elsevier2010

Nonholonomic source seeking in switching random fields

Mahmut Selman Sakar

We consider the problem of designing controllers for nonholonomic mobile robots converging to the source (minimum) of a field. In addition to the mobility constraints posed by the nonholonomic dynamics, we assume that the field is completely unknown to the ...

2010

Fast hard thresholding with Nesterov's gradient method

Volkan Cevher, Sina Jafarpour

We provide an algorithmic framework for structured sparse recovery which unifies combinatorial optimization with the non-smooth convex optimization framework by Nesterov [1, 2]. Our algorithm, dubbed Nesterov iterative hard-thresholding (NIHT), is similar ...

2010

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

Alireza Karimi, Mark Edward John Butcher

In this paper it is shown how Stochastic Approximation theory can be used to derive and analyse well-known Iterative Learning Control algorithms for linear systems. The Stochastic Approximation theory gives conditions that, when satisfied, ensure almost su ...

Springer2010

Optimizing evacuation instructions while anticipating traveler compliance behavior

Instructing evacuees on their departure time, destination and route can lead to more efficient traffic operations. Empirical findings on evacuation behavior support the view that in practice a share of travelers decides not to comply, while current evacuat ...

2010

Geometry-aware analysis of high-dimensional visual information sets

Effrosyni Kokiopoulou

Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...

EPFL2009

Minimum distance between pattern transformation manifolds: Algorithm and Applications

Pascal Frossard, Effrosyni Kokiopoulou

Transformation invariance is an important property in pattern recognition, where different observations of the same object typically receive the same label. This paper focuses on a transformation invariant distance measure that represents the minimum dista ...

2009

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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An optimal first-order solver for the TV-$L_1$ optical flow problem

An Adaptive Initialization Method for Speaker Diarization based on Prosodic Features

An Adaptive Initialization Method for Speaker Diarization based on Prosodic Features

Maximizing the net present value of a project under uncertainty

Nonholonomic source seeking in switching random fields

Fast hard thresholding with Nesterov's gradient method

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

Optimizing evacuation instructions while anticipating traveler compliance behavior

Geometry-aware analysis of high-dimensional visual information sets

Minimum distance between pattern transformation manifolds: Algorithm and Applications

An Adaptive Initialization Method for Speaker Diarization based on Prosodic Features

Nonholonomic source seeking in switching random fields

An Adaptive Initialization Method for Speaker Diarization based on Prosodic Features

Maximizing the net present value of a project under uncertainty

An optimal first-order solver for the TV-$L_1$ optical flow problem

Geometry-aware analysis of high-dimensional visual information sets

Optimizing evacuation instructions while anticipating traveler compliance behavior

Fast hard thresholding with Nesterov's gradient method

Minimum distance between pattern transformation manifolds: Algorithm and Applications

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System