Information theoretic feature extraction for audio-visual speech recognition

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In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

Connectivity between the hyporheic zone and the flow is essential for the development of benthos and the reproductive success of spawning fish. The infiltration of fine sediment leads to clogging of the riverbed, reducing porosity and vertical water exchan ...

One of the most classical results in high-dimensional learning theory provides a closed-form expression for the generalisation error of binary classification with a single-layer teacher-student perceptron on i.i.d. Gaussian inputs. Both Bayes-optimal (BO) ...

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

We consider the idealized setting of gradient flow on the population risk for infinitely wide two-layer ReLU neural networks (without bias), and study the effect of symmetries on the learned parameters and predictors. We first describe a general class of s ...

The resilience of the mitochondrial genome (mtDNA) to a high mutational pressure depends, in part, on negative purifying selection in the germline. A paradigm in the field has been that such selection, at least in part, takes place in primordial germ cells ...

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across similar to 15 000deg(2) of the sky. Euclid is expected to detect similar to 12 billion astronomical source ...

This paper presents explicit solutions for two related non-convex information extremization problems due to Gray and Wyner in the Gaussian case. The first problem is the Gray-Wyner network subject to a sum-rate constraint on the two private links. Here, ou ...

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

Supervised and unsupervised kernel-based algorithms widely used in the physical sciences depend upon the notion of similarity. Their reliance on pre-defined distance metrics-e.g. the Euclidean or Manhattan distance-are problematic especially when used in c ...

Information theoretic feature extraction for audio-visual speech recognition

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Improving Generalization of Pretrained Language Models

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Impact of substrate clogging on vertical connectivity

Learning curves for the multi-class teacher-student perceptron

Robust Outlier Rejection for 3D Registration with Variational Bayes

On the symmetries in the dynamics of wide two-layer neural networks

Reanalysis of mtDNA mutations of human primordial germ cells (PGCs) reveals NUMT contamination and suggests that selection in PGCs may be positive

Euclid preparation XXII. Selection of quiescent galaxies from mock photometry using machine learning

The Gray-Wyner Network and Wyner's Common Information for Gaussian Sources

A Functional Perspective on Information Measures

Metric learning for kernel ridge regression: assessment of molecular similarity