Publication

An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation

Related publications (42)

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.

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Volkan Cevher, Anastasios Kyrillidis

The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the

\ell_2

-data error objective and the

\ell_1

-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection ...

IEEE2012

FAST TV-L1 OPTICAL FLOW FOR INTERACTIVITY

Pierre Vandergheynst, Gilles Puy, Emmanuel D'Angelo, Johann Paratte

Vision is a natural tool for human-computer interaction, since it pro- vides visual feedback to the user and mimics some human behaviors. It requires however the fast and robust computation of motion primi- tives, which remains a difficult problem. In this ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

A heuristic for nonlinear global optimization relevant to discrete choice models estimation

Michel Bierlaire, Michaël Clément Louis Ghislain Thémans, Nicolas Zufferey

In most applications related to transportation, it is of major importance to be able to identify the global optimum of the associated optimization problem. The work we present in this paper is motivated by the optimization problems arising in the maximum l ...

2007

Impact of Sample Sizes on Information Theoretic Measures for Audio-Visual Signal Processing

Jean-Philippe Thiran, Ninoslav Marina, Ivana Arsic de Heras Ciechomska

In this paper we aim to explore what is the most appropriate number of data samples needed when measuring the temporal correspondence between a chosen set of video and audio cues in a given audio-visual sequence. Presently the optimal model that connects s ...

IEEE2005

Optimum error nonlinearities for long adaptive filters

Ali H. Sayed

In this paper, we consider the class of adaptive filters with error nonlinearities. In particular, we derive an expression for the optimum nonlinearity that minimizes the steady-state error and attains the limit mandated by the Cramer-Rae bound of the unde ...

2002

Mixtures of latent variable models for density estimation and classification

This paper deals with the problem of probability density estimation with the goal of finding a good probabilistic representation of the data. One of the most popular density estimation methods is the Gaussian mixture model (GMM). A promising alternative to ...

IDIAP2000

Mixture models for unsupervised and supervised learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of al1 this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

EPFL2000

Mixture Models for Unsupervised and Supervised Learning

In a society which produces and consumes an ever increasing amount of information, methods which can make sense out of all this data become of crucial importance. Machine learning tries to develop models which can make the information load accessible. Thre ...

IDIAP2000

Mixture Models for Unsupervised and Supervised Learning

École Polytechnique Fédérale de Lausanne, Computer Science Department2000

Monotonicity Constraints in the Estimation of Distributions with Smoothing Splines

Eva Maria Restle

A non-parametric method of distribution estimation for univariate data is presented. The idea is to adapt the smoothing spline procedure used in regression to the estimation of distributions via a scatterplot smoothing of theempirical distribution function ...

2000