Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing [PDF]
Neural Information Processing Systems, 2023 Transformer models have been widely adopted in various domains over the last years, and especially large language models have advanced the field of AI significantly. Due to their size, the capability of these networks has increased tremendously, but this
Yelysei Bondarenko +2 more
semanticscholar +1 more source
Testing for outliers with conformal p-values [PDF]
Annals of Statistics, 2021 This paper studies the construction of p-values for nonparametric outlier detection, taking a multiple-testing perspective. The goal is to test whether new independent samples belong to the same distribution as a reference data set or are outliers.
Stephen Bates +4 more
semanticscholar +1 more source
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Active learning promises to alleviate the massive data needs of supervised machine learning: it has successfully improved sample efficiency by an order of magnitude on traditional tasks like topic classification and object recognition.
Siddharth Karamcheti +3 more
semanticscholar +1 more source
Addressing COVID-19 Outliers in BVARs with Stochastic Volatility
Review of Economics and Statistics, 2021 The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard Bayesian vector autoregressions (BVARs). To address these issues, we propose BVAR models with outlier-augmented stochastic volatility (SV)
Andrea Carriero +3 more
semanticscholar +1 more source
PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds [PDF]
Computer graphics forum (Print), 2019 Point clouds obtained with 3D scanners or by image‐based reconstruction techniques are often corrupted with significant amount of noise and outliers. Traditional methods for point cloud denoising largely rely on local surface fitting (e.g.
Marie-Julie Rakotosaona +4 more
semanticscholar +1 more source
Comparative Analysis of Machine Learning-Based Approaches for Anomaly Detection in Vehicular Data
Vehicles, 2021 The rapid growth of demand for transportation, both for people and goods, as well as the massive accumulation of population in urban centers has augmented the need for the development of smart transport systems.
Konstantinos Demestichas +3 more
doaj +1 more source
Free cyclic submodules in the context of the projective line [PDF]
, 2015 We discuss the free cyclic submodules over an associative ring $R$ with unity. Special attention is paid to those, which are generated by outliers. This paper describes all orbits of such submodules in the ring of lower triangular $3$x$3$ matrices over a
Bartnicka, Edyta, Matras, Andrzej
core +2 more sources
Ultimately Bounded Filtering Subject to Impulsive Measurement Outliers
IEEE Transactions on Automatic Control, 2021 This article is concerned with the ultimately bounded filtering problem for a class of linear time-delay systems subject to norm-bounded disturbances and impulsive measurement outliers (IMOs).
Lei Zou +3 more
semanticscholar +1 more source
ROBIN: a Graph-Theoretic Approach to Reject Outliers in Robust Estimation using Invariants [PDF]
IEEE International Conference on Robotics and Automation, 2020 Many estimation problems in robotics, computer vision, and learning require estimating unknown quantities in the face of outliers. Outliers are typically the result of incorrect data association or feature matching, and it is not uncommon to have ...
J. Shi, Heng Yang, L. Carlone
semanticscholar +1 more source
Evaluation of Calibration Equations by Using Regression Analysis: An Example of Chemical Analysis
Sensors, 2022 A calibration curve is used to express the relationship between the response of the measuring technique and the standard concentration of the target analyst.
Hsuan-Yu Chen, Chiachung Chen
doaj +1 more source