arXiv research

New ensemble models classify mouse movement trajectories to assess survey question difficulty.

Surveying low-cost sensors for air quality monitoring and calibration.

Online crowdsourcing provides a scalable and inexpensive means to collect knowledge (e.g. labels) about various types of data items (e.g. text, audio, video). However, it is also known to result in large variance in the quality of recorded responses which often cannot be directly used for training machine learning syst…

Survey examines data quality challenges in edge ML.

Survey on ML for wireless network optimization across PHY, MAC, and network layers.

Survey of self-supervised image representation learning methods.

Online surveys have the potential to support adaptive questions, where later questions depend on earlier responses. Past work has taken a rule-based approach, uniformly across all respondents. We envision a richer interpretation of adaptive questions, which we call dynamic question ordering (DQO), where question order …

Survey of deep RL in intelligent transportation systems.

Survey on concept factorization methods for better feature learning.

Automatically identifies RRLyrae stars from VVV survey data.

Survey on deep learning robust training methods for noisy labels.

Understanding the nature of dark energy, the mysterious force driving the accelerated expansion of the Universe, is a major challenge of modern cosmology. The next generation of cosmological surveys, specifically designed to address this issue, rely on accurate measurements of the apparent shapes of distant galaxies. H…

User surveys for Quality of Experience (QoE) are a critical source of information. In addition to the common "star rating" used to estimate Mean Opinion Score (MOS), more detailed survey questions (problem tokens) about specific areas provide valuable insight into the factors impacting QoE. This paper explores two aspe…

AI enhances ESG practices in finance, but requires careful consideration.

Survey on random features for kernel approximation, focusing on algorithms, theory, and practical applications.

CatSIM measures image similarity robustly to small changes.

Survey categorizes methods for learning state representations in reinforcement learning.

Survey of data augmentation methods for improving deep learning on time series data.

Machine learning improves official statistics but needs rigorous validation.

The study maps ML quality dimensions to fairness, enhancing the QF4SA framework.

Little is known about how different types of advertising affect brand attitudes. We investigate the relationships between three brand attitude variables (perceived quality, perceived value and recent satisfaction) and three types of advertising (national traditional, local traditional and digital). The data represent t…

The UN Sustainable Development Goals allude to the importance of infrastructure quality in three of its seventeen goals. However, monitoring infrastructure quality in developing regions remains prohibitively expensive and impedes efforts to measure progress toward these goals. To this end, we investigate the use of wid…

Smartphone data shows promise but accuracy issues remain.

Survey of software developers' experience with Github Copilot tool.

PICZL improves photometric redshifts for AGN in all-sky surveys.

Survey compares methods for generating artificial outliers.

This paper surveys large-scale machine learning methods for efficient data analysis.

This research evaluates the quality of unsupervised embeddings using linear separability metrics.

Survey of alignment techniques for large language models.

Mobile and ubiquitous sensing of urban air quality has received increased attention as an economically and operationally viable means to survey atmospheric environment with high spatial-temporal resolution. This paper proposes a machine learning based mobile air pollution sensing framework, called Deep-MAPS, and demons…

This paper gives a review and synthesis of methods of evaluating dimensionality reduction techniques. Particular attention is paid to rank-order neighborhood evaluation metrics. A framework is created for exploring dimensionality reduction quality through visualization. An associated toolkit is implemented in R. The to…

The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion. While much of the earlier research was focused on identification of fake news based on its contents or by exploiting …

New method improves active statistical inference by reducing noise.

The paper proposes incentivizing human annotators with 'golden questions' to improve data quality.

How are economic activities linked to geographic locations? To answer this question, we use a data-driven approach that builds on the information about location, ownership and economic activities of the world's 3,000 largest firms and their almost one million subsidiaries. From this information we generate a bipartite …

Clever sampling methods can be used to improve the handling of big data and increase its usefulness. The subject of this study is remote sensing, specifically airborne laser scanning point clouds representing different classes of ground cover. The aim is to derive a supervised learning model for the classification usin…

Machine learning detects survey validity from user behavior.

Entity resolution (ER) is the task of identifying records belonging to the same entity (e.g. individual, group) across one or multiple databases. Ironically, it has multiple names: deduplication and record linkage, among others. In this paper we survey metrics used to evaluate ER results in order to iteratively improve…

Survey updates knowledge on homogeneous Einstein spaces.

Survey on submanifolds in nearly Kähler spaces.

Survey of minimal genus problem progress.

The paper improves Lasso inference methods for survey data.

Combines k-means and hill climbing for stratification and allocation.

Survey on L^2-invariants for 3-manifolds.

In the past few years, neural abstractive text summarization with sequence-to-sequence (seq2seq) models have gained a lot of popularity. Many interesting techniques have been proposed to improve seq2seq models, making them capable of handling different challenges, such as saliency, fluency and human readability, and ge…

Survey on DDVV-type inequalities, their history, and recent developments.

Survey on distributed machine learning to handle large data.

SaML guides ML models to avoid survey biases.