Batch Universal Prediction

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In recent years statistical physics has proven to be a valuable tool to probe into large dimensional inference problems such as the ones occurring in machine learning. Statistical physics provides analytical tools to study fundamental limitations in their ...

Recently, large pretrained language models have demonstrated strong language understanding capabilities. This is particularly reflected in their zero-shot and in-context learning abilities on downstream tasks through prompting. To assess their impact on sp ...

We propose an information theoretic framework for quantitative assessment of acoustic models used in hidden Markov model (HMM) based automatic speech recognition (ASR). The HMM backend expects that (i) the acoustic model yields accurate state conditional e ...

The design of reliable wearable technologies for real-time and long-term monitoring presents a major challenge. Self-awareness is a promising solution that enables the system to monitor itself in interaction with the environment and to manage its resources ...

Decentralized training of deep learning models is a key element for enabling data privacy and on-device learning over networks, as well as for efficient scaling to large compute clusters. As current approaches are limited by network bandwidth, we propose t ...

Consider a receiver that observes multiple interfering codewords. The compute-and-forward technique makes it possible for the receiver to directly decode linear combinations of the codewords. Previous work has focused on compute-and-forward for linear Gaus ...

This study analyses the use of neural networks to produce accurate forecasts of total bookings and cancellations before departure, of a major European rail operator. Effective forecasting models, can improve revenue performance of transportation companies ...

Exploratory search over a collection often requires users to iteratively apply a variety of strategies, such as searching for more general or more specific concepts in reaction to the information they encounter. Rich semantic models, such as WordNet, are p ...

Batch Universal Prediction

Chattez avec Graph Search

Sparse representations, inference and learning

Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Self-Aware Machine Learning for Multimodal Workload Monitoring During Manual Labor on Edge Wearable Sensors

Decentralized deep learning with arbitrary communication compression

Compute-and-forward for discrete memoryless networks

Railway demand forecasting in revenue management using neural networks

Concept expansion using semantic fisheye views