Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

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.

We consider the problem of parameter estimation in a Bayesian setting and propose a general lower-bound that includes part of the family of f-Divergences. The results are then applied to specific settings of interest and compared to other notable results i ...

There are increasing interests in document layout representation learning and understanding. Transformer, with its great power, has become the mainstream model architecture and achieved promising results in this area. As elements in a document layout consi ...

The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

Soft Magnetic Composites (SMCs) have huge application potential in electrical devices. With the development of additive manufacturing (AM), the properties of SMCs can be boosted. It is therefore required an optimization algorithm to design SMCs considering ...

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections. A few examples where this problem is relevant are compressed sensing, sparse superposition codes, and code division multiple access. There has been a ...

Backdoor attacks allow an attacker to embed functionality jeopardizing proper behavior of any algorithm, machine learning or not. This hidden functionality can remain inactive for normal use of the algorithm until activated by the attacker. Given how steal ...

Given two probability measures P and Q and an event E, we provide bounds on P(E) in terms of Q(E) and f-divergences. In particular, the bounds are instantiated when the measures considered are a joint distribution and the corresponding product of marginals ...

As the usage of FPGAs spreads, engineers will inevitably employ them in ways unforeseen-or unwanted-by their manufacturers. Xilinx's toolchains offer multiple points for customizing the FPGA compilation flow, but all flows must end with Vivado as it is the ...

State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. While effective, these data-driven approaches rely on large amount of data annotation to achieve good performance, which stops these models from ...

The following problem is considered: given a joint distribution P XY and an event E, bound P XY (E) in terms of P X P Y (E) (where P X P Y is the product of the marginals of P XY ) and a measure of dependence of X and Y. Such bounds have direct application ...

In this work, we present a simple biometric indexing scheme which is binning and retrieving cancelable deep face templates based on frequent binary patterns. The simplicity of the proposed approach makes it applicable to unprotected as well as protected, i ...

This thesis is devoted to information-theoretic aspects of community detection. The importance of community detection is due to the massive amount of scientific data today that describes relationships between items from a network, e.g., a social network. I ...

Transaction processing is a central part of most database applications. While serializability remains the gold standard for desirable transactional semantics, many database systems offer improved transaction throughput at the expense of introducing potenti ...

We examine a class of stochastic deep learning models with a tractable method to compute information-theoretic quantities. Our contributions are three-fold: (i) we show how entropies and mutual informations can be derived from heuristic statistical physics ...

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families ...

Evans et al. [1] proved the subadditivity of the mutual information in the broadcasting on tree model with binary vertex labels and symmetric edge channels. They raised the question of whether such subadditivity extends to loopy graphs in some appropriate ...

In this paper, we study the compression of a target two-layer neural network with N nodes into a compressed network with M < N nodes. More precisely, we consider the setting in which the weights of the target network are i.i.d. sub-Gaussian, and we minimiz ...

Feature selection problems arise in a variety of applications, such as microarray analysis, clinical prediction, text categorization, image classification and face recognition, multi-label learning, and classification of internet traffic. Among the various ...

Kinetic models of metabolism relate metabolic fluxes, metabolite concentrations and enzyme levels through mechanistic relations, rendering them essential for understanding, predicting and optimizing the behaviour of living organisms. However, due to the la ...

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its mutual information when the tensor is of even order. The proof uses the adaptive interpolation method, for which rank-on ...

Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

Chattez avec Graph Search

Lower-bounds on the Bayesian Risk in Estimation Procedures via f–Divergences

Exploring Heterogeneous Feature Representation for Document Layout Understanding

Robust Generalization via $\alpha$-Mutual Information

Topology Optimization of Soft Magnetic Composites with Integer Programming

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

An anomaly detection approach for backdoored neural networks: face recognition as a case study

Robust Generalization via f−Mutual Information

Bitfiltrator: A general approach for reverse-engineering Xilinx bitstream formats

Leveraging Self-Supervision for Cross-Domain Crowd Counting

Strengthened Information-theoretic Bounds on the Generalization Error

Indexing Protected Deep Face Templates by Frequent Binary Patterns

Statistical Physics Methods for Community Detection

Robustness Against Read Committed: A Free Transactional Lunch

Entropy and mutual information in models of deep neural networks

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Subadditivity Beyond Trees and the Chi-Squared Mutual Information

Sharp asymptotics on the compression of two-layer neural networks

Theoretical foundations of forward feature selection methods based on mutual information

Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks

Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization