Concept

Data preparation

Related publications (11)

Robust NAS under adversarial training: benchmark, theory, and beyond

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Yongtao Wu

Recent developments in neural architecture search (NAS) emphasize the significance of considering robust architectures against malicious data. However, there is a notable absence of benchmark evaluations and theoretical guarantees for searching these robus ...

2024

A Machine Learning-based Framework for Forecasting Sales of New Products With Short Life Cycles Using Deep Neural Networks

Ralf Seifert, Yara Kayyali El Alem

Demand forecasting is becoming increasingly important as firms launch new products with short life cycles more frequently. This paper provides a framework based on state-of-the-art techniques that enables firms to use quantitative methods to forecast sales ...

2022

Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure Detection

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Hyperdimensional computing is a promising novel paradigm for low-power embedded machine learning. It has been applied on different biomedical applications, and particularly on epileptic seizure detection. Unfortunately, due to differences in data preparati ...

2021

Holistic, Efficient, and Real-time Cleaning of Heterogeneous Data

Styliani Asimina Giannakopoulou

Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. Existing solutions that attempt to automate t ...

EPFL2021

Seismic Vulnerability Assessment at Large Scale – City of Geneva

Babak Haftgoli Bakhtiari

In order to evaluate the seismic vulnerability at large scale, it is necessary to gain awareness of the soil properties, types of materials used in the construction of buildings during different periods, the construction standards of each period, different ...

2020

Abstract Text Summarization: A Low Resource Challenge

Petr Motlicek

Text summarization is considered as a challenging task in the NLP community. The availability of datasets for the task of multilingual text summarization is rare, and such datasets are difficult to construct. In this work, we build an abstract text summari ...

Association for Computational Linguistics (ACL)2019

Adaptive data augmentation for image classification

Pascal Frossard, Alhussein Fawzi

Data augmentation is the process of generating samples by transforming training data, with the target of improving the accuracy and robustness of classifiers. In this paper, we propose a new automatic and adaptive algorithm for choosing the transformations ...

IEEE2016

Runtime Prediction for Scale-Out Data Analytics

Adrian Daniel Popescu

Many analytics applications generate mixed workloads, i.e., workloads comprised of analytical tasks with different processing characteristics including data pre-processing, SQL, and iterative machine learning algorithms. Examples of such mixed workloads ca ...

EPFL2015

Cost Effective Real-Time Traffic Signal Control Using the TUC Strategy

Real-time urban traffic control systems frequently require precise traffic measurements and fast communications in order to achieve desired performance levels. Such requirements may hinder the adoption of these beneficial control systems because of the ins ...

2010

Pay no attention to the alternatives behind the curtain: demand forecasting with missing data

Jeffrey Newman

Discrete choice modeling advances abound for scenarios where we can collect data about the behaviors of individuals, and observe their ultimate choice from among the range of possible alternatives. However, particularly in competitive private sector enterp ...

2009

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