Publications related to Batch Universal Prediction

Related publications (8)

Sparse representations, inference and learning

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 ...

IOP Publishing Ltd2024

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

Mutian He

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 ...

Isca-Int Speech Communication Assoc2023

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

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

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 ...

ELSEVIER2020

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

David Atienza Alonso, Amir Aminifar, Adriana Arza Valdes, Farnaz Forooghifar, Giulio Masinelli

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 ...

2020

Decentralized deep learning with arbitrary communication compression

Martin Jaggi, Sebastian Urban Stich, Tao Lin, Anastasiia Koloskova

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 ...

2019

Compute-and-forward for discrete memoryless networks

Michael Christoph Gastpar

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 ...

2014

Railway demand forecasting in revenue management using neural networks

Shadi Sharif Azadeh

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 ...

2013

Concept expansion using semantic fisheye views

Pearl Pu Faltings, Vincent Jean Fabrice Schickel, Frank Paul Janecek

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 ...

Springer Verlag, Heidelberg, D-69121, Germany2005