Science topic

Bias (Epidemiology) - Science topic

Any deviation of results or inferences from the truth, or processes leading to such deviation. Bias can result from several sources: one-sided or systematic variations in measurement from the true value (systematic error); flaws in study design; deviation of inferences, interpretations, or analyses based on flawed data or data collection; etc. There is no sense of prejudice or subjectivity implied in the assessment of bias under these conditions.
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Publications related to Bias (Epidemiology) (10,000)
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Objectives The aim of this research is to examine the developmental stages of acquiring stress in the speech of Ammani Arabic-speaking children (henceforth AASC). Methods Elicited and spontaneous speech productions of 48 typically developing children were transcribed and coded with the primary stress. Words were also analyzed according to their me...
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In the spring of 2022, an excessive amount of rainfall fell in Southwest China (SWC) under the background of frequent droughts in history. This extreme event occurred in the decaying phase of a second-year of a double/triple dip La Nina event, and thus, presumably La Niña played a role in this extreme event. In this work, based on observational dia...
Article
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Combining the results of two empirical studies, we investigate the role of alters’ motivation in explaining change in ego’s network position over time. People high in communal motives, who are prone to supportive and altruistic behavior in their interactions with others as a way to gain social acceptance, prefer to establish ties with co-workers oc...
Conference Paper
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Recent research using machine decision makers has revealed that some leading interactive evolutionary multi-objective optimization algorithms do not perform robustly with respect to interactions with preference models (and biases) posited to be representative of human Decision Makers (DMs). In order to model preferences better, we propose an explai...
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To date, graph collaborative filtering (CF) strategies have been shown to outperform pure CF models in generating accurate recommendations. Nevertheless, recent works have raised concerns about fairness and potential biases in the recommendation landscape since unfair recommendations may harm the interests of Consumers and Producers (CP). Acknowled...
Article
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Keywords are often used to shed light on shared words and their meanings, including their contestation. Often these are determined using small samples or author inferences. However, identification large sample, data-driven keywords is important for writing studies to avoid a range of biases including socioeconomic, confirmation, sampling. We use th...
Conference Paper
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Während das generische Maskulinum im Deutschen traditionell als geschlechtsneutral angesehen wird (Doleschal, 2002), zeigen Studien der vergangenen Jahrzehnte, dass diese Annahme der Geschlechtsneutralität nicht zutrifft (z.B. Stahlberg & Sczesny 2001; Gygax et al. 2008; Irmen & Kurovskaja 2010; Misersky, Majid & Snijders 2019). Anstatt einer gesch...
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In a series of ten preregistered experiments (N = 2043), we investigate the effect of outcome valence on judgments of probability, negligence, and culpability – a phenomenon sometimes labelled moral (and legal) luck. We found that harmful outcomes, when contrasted with neutral outcomes, lead to an increased perceived probability of harm ex post, an...
Article
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Maximal Lactate steady-state (MLSS) demarcates sustainable from unsustainable exercise and is used for evaluation/monitoring of exercise capacity. Still, its determination is physically challenging and time-consuming. This investigation aimed at validating a simple, submaximal approach based on blood lactate accumulation ([∆lactate]) at the third m...
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To simulate seismic wavefields with a frequency-domain wave equation, conventional numerical methods must solve the equation sequentially to obtain the wavefields for different frequencies. The monofrequency equation has the form of a Helmholtz equation. When solving the Helmholtz equation for seismic wavefields with multiple frequencies, a physics...
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We observed dislocations in β-Ga2O3 Schottky barrier diodes (SBD) using synchrotron X-ray topography (XRT) and studied their behaviors under forward or reverse bias. Several representative dislocation types were identified by observing the dislocation lines and their Burgers vectors. After comparing the XRT images taken before and after the bias wa...
Article
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This study investigates how executives' financial experience (EFE) impacts myopic marketing management (MMM) from a myopic loss aversion (MLA) perspective and ways to mitigate the strategic bias induced by personal cognitive bias. It discovers that executives with financial sector working experience and educational experience are positively associa...
Article
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It has been proposed that emotional intelligence (EI) functions as a magnifier of emotional experience. This phenomenon, called the "hypersensitivity hypothesis," predicts that high EI amplifies the emotional aspects of experience (Fiori & Ortony, 2021). We tested whether high EI individuals show stronger attention to emotional than neutral express...
Article
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Human faces convey essential information for understanding others’ mental states and intentions. The importance of faces in social interaction has prompted suggestions that some relevant facial features such as configural information, emotional expression, and gaze direction may promote preferential access to awareness. This evidence has predominan...
Article
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Tropospheric delay is one of the major error sources in global navigation satellite systems (GNSS). The position accuracy determined using GNSS depends on the satellite’s geometry factor. However, in low elevation angle GNSS signals have a high tropospheric slant delay error and need a good mapping function model to cover this error. In this paper,...
Article
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Purpose This paper focusses on demonstrating the role of social media engagement and considering emotional intelligence (hereafter EI) as a critical concept to successful employment, mainly when individuals fail to reach the desired employment despite “meeting” the role requirements. Design/methodology/approach The authors adopted a qualitative ap...
Article
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This paper aimed to introduce the GapMET software, developed by the authors, and evaluate the accuracy of its six methods for gap-filling the main meteorological variables monitored by weather station in the state of Mato Grosso, Brazil, using reference time series from neighbour weather station and/or remote sensing products. The methods were test...
Article
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An 1500nm thick collector layer is adopted in the uni-travelling-carrier photodiode (UTC-PD) to reduce the PD's capacitance, while the PD's diameter is set to be 20μm for better saturation performance and optical coupling characteristic of a signal from a single mode fiber. By optimizing biasing voltage and input light intensity, the electric field...
Article
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Neglecting the role of political bias in the public’s perceptions of health authorities could be deceptive when studying potentially politicized COVID-19 conspiracy theories (CCTs); however, previous studies often treated health authorities as a single entity and did not distinguish between different types of CCTs. Drawing from motivated reasoning...
Article
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Empirical Dynamic Modeling (EDM) has been a powerful tool for complex ecosystem prediction by providing an equation-free modelling framework. Theoretically, it allows future ecosystem behavior to be predicted by connecting current state to the similar, adjacent and future state on the attractor manifold which is reconstructed by single or multiple...
Article
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Learning an unbiased classifier from imbalanced image datasets is challenging since the classifier may be strongly biased toward the majority class. To address this issue, some generative model-based oversampling methods have been proposed. However, most of these methods pay little attention to boundary samples, which may contribute tiny to learnin...
Article
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To date, numerous nucleotide, amino acid, and codon substitution models have been developed to estimate the evolutionary history of any sequence/organism in a more comprehensive way. Out of these three, the codon substitution model is the most powerful. These models have been utilized extensively to detect selective pressure on a protein, codon usa...
Article
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Previous research has hypothesized default interpretive biases for three types of ambiguities with English logical words and, or, and not. First, disjunction (A or B) is hypothesized to be biased towards an exclusive interpretation in upward-entailing environments and an inclusive interpretation in downward-entailing environments (Levinson 2000, Ch...
Article
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Background Structural variation (SV), which ranges from 50 bp to $$\sim$$ ∼ 3 Mb in size, is an important type of genetic variations. Deletion is a type of SV in which a part of a chromosome or a sequence of DNA is lost during DNA replication. Three types of signals, including discordant read-pairs, reads depth and split reads, are commonly used fo...
Article
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Tree ensemble algorithms, such as random forest (RF), are some of the most widely applied methods in machine learning. However, an important hyperparameter, the number of classification or regression trees within the ensemble must be specified in these algorithms. The number of trees within the ensemble can adversely affect bias or computational co...
Article
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Politicians regularly bargain with colleagues and other actors. Bargaining dynamics are central to theories of legislative politics and representative democracy, bearing directly on the substance and success of legislation, policy, and on politicians’ careers. Yet, controlled evidence on how legislators bargain is scarce. Do they apply different st...
Article
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This literature review research paper examines the application of AI and machine learning in the financial industry and its effects on risk management and fraud detection. The study conducts a comprehensive search of academic and industry sources and identifies key findings and trends related to the use of these technologies in the financial indust...
Article
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Using a nonperturbative classical approach, we study the dynamics of a mobile particle interacting with an infinite one-dimensional (1D) chain of harmonic oscillators. This minimal system is an effective model for many 1D transport phenomena, such as molecular motion in nanotubes and ionic conduction through solid-state materials. As expected, coup...
Article
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В статье экспериментально доказана значимость учета дифференциальных кодовых задержек (ДКЗ) (Differential Code Bias) при определении координат методом Precise Point Positioning (PPP) по данным многосистемных ГНСС-измерений (GPS, ГЛОНАСС, Galileo). Благодаря учету ДКЗ существенно сокращается время сходимости навигационного решения. Описаны потребова...
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In this study, a physics-informed neural energy-force network (PINEFN) framework is first proposed to directly solve the optimum design of truss structures that structural analysis is completely removed from the implementation of the global optimization. Herein, a loss function is constructed to guide the training network based on the complementary...
Article
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Investigation of the inherent field-driven charge transport behaviour of three-dimensional lead halide perovskites has largely remained challenging, owing to undesirable ionic migration effects near room temperature and dipolar disorder instabilities prevalent specifically in methylammonium-and-lead-based high-performing three-dimensional perovskit...
Article
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Although faces of in-group members are generally thought to be processed holistically, there are mixed findings on whether holistic processing remains robust for faces of out-group members and what factors contribute to holistic processing of out-group faces. This study examined how implicit social bias, experience with out-group members, and abili...
Preprint
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Counterfactual explanations play an important role in detecting bias and improving the explainability of data-driven classification models. A counterfactual explanation (CE) is a minimal perturbed data point for which the decision of the model changes. Most of the existing methods can only provide one CE, which may not be achievable for the user. I...
Article
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This study investigates the impact of information uncertainty on analysts' earnings forecasts for a sample of European companies from 2010 to 2019. We argue that representativeness, anchoring and adjustment, and leniency biases jointly influence analysts' forecasts and lead to optimism. We suggest that uncertainty boosts analysts’ optimism as behav...
Article
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Resumo O texto busca trazer uma abordagem contemporânea acerca da ideia de representação na arquitetura, através de autores que tensionam o entendimento da obra como veiculo de significa-ção e permanência. Trata-se de uma concepção de arquitetura mais relacionada ao tempo do que ao espaço, onde a forma é deliberadamente suplantada pela experiência....
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Optimization of Josephson oscillators requires a quantitative understanding of their microwave properties. A Josephson junction has a geometry similar to a microstrip patch antenna. However, it is biased by a dc current distributed over the whole area of the junction. The oscillating electric field is generated internally via the ac-Josephson effec...
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The features of the electroluminescence spectra of narrow-gap type II InAs/InSb/InAs heterostructures containing a single layer of InSb quantum dots placed into the p-n-InAs junction were studied. The luminescent properties of the heterostructures under a forward and reverse bias in the temperature range of 77–300 K were investigated as a function...
Article
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The early, valid prediction of heart problems would minimize life threats and save lives, while lack of prediction and false diagnosis can be fatal. Addressing a single dataset alone to build a machine learning model for the identification of heart problems is not practical because each country and hospital has its own data schema, structure, and q...
Article
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To solve the problem of false tracks generated by breakdowns and clutter in point-target tracking in polar coordinates, a fusion tracking algorithm based on a converted measurement Kalman filter and random matrix expansion is proposed. The converted measurement Kalman filter (CMKF) transforms the polar coordinate data of the target at the current t...
Article
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Hydroacoustics is a non-invasive fish stock assessment sampling technique that plays an important role in fishery science and management. However, non-standard hydroacoustic surveys could lead to biased results, and the factor of the sampling period (e.g., season and diel cycle) is extremely critical as it can greatly affect hydroacoustic results....
Preprint
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We propose a simplicial complex convolutional neural network (SCCNN) to learn data representations on simplicial complexes. It performs convolutions based on the multi-hop simplicial adjacencies via common faces and cofaces independently and captures the inter-simplicial couplings, generalizing state-of-the-art. Upon studying symmetries of the simp...
Article
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Modern social sciences arose during a period of classical modernity in which discovering universal rules between distinct phenomena was the most prominent criterion of scientific knowledge. Social phenomena were considered in the form of isolated, determined, standardized, and regulated objects whose knowledge, like that of the natural sciences, de...
Preprint
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Combining training data from multiple sources increases sample size and reduces confounding, leading to more accurate and less biased machine learning models. In healthcare, however, direct pooling of data is often not allowed by data custodians who are accountable for minimizing the exposure of sensitive information. Federated learning offers a pr...
Article
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Tactics to determine the emotions of authors of texts such as Twitter messages often rely on multiple annotators who label relatively small data sets of text passages. An alternative method gathers large text databases that contain the authors’ self-reported emotions, to which artificial intelligence, machine learning, and natural language processi...
Article
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Background The strength of cotton fiber has been extensively studied and significantly improved through selective breeding, but fiber elongation has largely been ignored, even though elongation contributes to determining the energy needed to break fibers. Recent developments to calibrate the high volume instrument (HVI) for elongation has renewed i...
Article
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Estimating the number of species in a community is important for assessments of biodiversity. Previous species richness estimators are mainly based on nonparametric approaches. Although parametric asymptotic models have been applied, they received limited attention due to specific limitations. Here, we introduce parametric models fitting the probab...
Article
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Training deep learning models on medical images heavily depends on experts’ expensive and laborious manual labels. In addition, these images, labels, and even models themselves are not widely publicly accessible and suffer from various kinds of bias and imbalances. In this paper, chest X-ray pre-trained model via self-supervised contrastive learnin...
Article
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Collaborative filtering recommender system (CFRS) plays a vital role in today’s e-commerce industry. CFRSs collect ratings from the users and predict recommendations for the targeted product. Conventionally, CFRS uses the user-product ratings to make recommendations. Often these user-product ratings are biased. The higher ratings are called push ra...
Article
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While quantum accelerometers sense with extremely low drift and low bias, their practical sensing capabilities face at least two limitations compared with classical accelerometers: a lower sample rate due to cold atom interrogation time; and a reduced dynamic range due to signal phase wrapping. In this paper, we propose a maximum likelihood probabi...
Preprint
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In random-effects models, hierarchical linear models, or multilevel models, it is typically assumed that the variances within higher-level units are homoscedastic, meaning that they are equal across these units. However, this assumption is often violated in research. Depending on the degree of violation, this can lead to biased standard errors of h...
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A directed acyclic graph (DAG) provides valuable prior knowledge that is often discarded in regression tasks in machine learning. We show that the independences arising from the presence of collider structures in DAGs provide meaningful inductive biases, which constrain the regression hypothesis space and improve predictive performance. We introduc...
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Toxic comment detection on social media has proven to be essential for content moderation. This paper compares a wide set of different models on a highly skewed multi-label hate speech dataset. We consider inference time and several metrics to measure performance and bias in our comparison. We show that all BERTs have similar performance regardless...
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The main advantage of an atomic accelerometer when compared to a classical accelerometer is negligible bias drift, allowing for stable long-term measurements, which opens the potential application in navigation. This negligible drift arises from the fact that the measurements can be traced back to natural constants, and the system is intrinsically...
Preprint
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Bayes factors for composite hypotheses have difficulty in encoding vague prior knowledge, leading to conflicts between objectivity and sensitivity including the Jeffreys-Lindley paradox. To address these issues we revisit the posterior Bayes factor, in which the posterior distribution from the data at hand is re-used in the Bayes factor for the sam...
Preprint
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This study analyzes the quality of simulated historical precipitation across the contiguous United States (CONUS) in a 12-km Weather Research and Forecasting model version 4.2.1 (WRF v 4.2.1)-based dynamical downscaling of the fifth generation ECMWF atmospheric reanalysis (ERA5). This work addresses the following questions: First, how well are the...
Article
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A plausible view about the epistemic condition of blameworthiness holds the following. Reasonable Expectation (RE): S's state of ignorance excuses iff S could not have been reasonably expected to have corrected or avoided the ignorance. An important, yet underexplored issue for RE concerns cases where an agent had the capacities and opportunities t...
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A major challenge of reinforcement learning (RL) in real-world applications is the variation between environments, tasks or clients. Meta-RL (MRL) addresses this issue by learning a meta-policy that adapts to new tasks. Standard MRL methods optimize the average return over tasks, but often suffer from poor results in tasks of high risk or difficult...
Article
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The stop-signal task is widely used in experimental psychology and cognitive neuroscience research, as well as neuropsycho-logical and clinical practice for assessing response inhibition. The task requires participants to make speeded responses on a majority of trials, but to inhibit responses when a stop signal appears after the imperative cue. Th...
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This paper proposes a simple method to distill and detect backdoor patterns within an image: \emph{Cognitive Distillation} (CD). The idea is to extract the "minimal essence" from an input image responsible for the model's prediction. CD optimizes an input mask to extract a small pattern from the input image that can lead to the same model output (i...
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Large language models have been shown useful in multiple domains including conversational agents, education , and explainable AI. ChatGPT is a large language model developed by OpenAI as a conversational agent. ChatGPT was trained on data generated by humans and by receiving human feedback. This training process results in a bias toward humans' tra...
Article
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Unlabelled: Achieving impact through research for development programmes (R4D) requires engagement with diverse stakeholders across the research, development and policy divides. Understanding how such programmes support the emergence of outcomes, therefore, requires a focus on the relational aspects of engagement and collaboration. Increasingly, e...
Article
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Alignment technology plays an important role in navigation, and is used extensively throughout military and civilian applications. However, the existing in-flight alignment methods cannot be applied to the low-cost based strap-down inertial navigation system/global positioning system integrated navigation system, used in short-endurance and high-sp...
Article
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YouTube is a popular social marketing platform. Marketers or advertisers can collaborate with a YouTube influencer to present marketing messages. However, negative user-generated comments may affect the effectiveness of message delivery. Thus, one pretest and two main studies were conducted to investigate the influence of negative comments on consu...
Article
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Over the past decades, long-term sequelae of burns have gained increasing attention. Women of childbearing age, who sustained abdominal burns earlier in life, may have unmet information needs on scar-related complications they can expect during pregnancy. We performed a review of the literature to identify abdominal, foetal, and potential other com...
Article
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The work presented in this paper focuses on developing a load-balanced user association scheme in a single Radio Access Technology (RAT) Heterogeneous Networks (HetNet). The optimization algorithm maximizes network capacity and optimal user association in a planned small cell deployment framework, considering Quality of Service (QoS) and network lo...
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Introduction Data imbalance is one of the crucial issues in big data analysis with fewer labels. For example, in real-world healthcare data, spam detection labels, and financial fraud detection datasets. Many data balance methods were introduced to improve machine learning algorithms' performance. Research claims SMOTE and SMOTE-based data-augmenta...
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Estimation of value in policy gradient methods is a fundamental problem. Generalized Advantage Estimation (GAE) is an exponentially-weighted estimator of an advantage function similar to $\lambda$-return. It substantially reduces the variance of policy gradient estimates at the expense of bias. In practical applications, a truncated GAE is used due...
Article
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Despite abundant accessible traffic data, researches on traffic flow estimation and optimization still face the dilemma of detailedness and integrity in the measurement. A dataset of city-scale vehicular continuous trajectories featuring the finest resolution and integrity, as known as the holographic traffic data, would be a breakthrough, for it c...
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Recent developments on a deep learning feed-forward network for estimating elliptic flow ($v_2$) coefficients in heavy-ion collisions have shown us the prediction power of this technique. The success of the model is mainly the estimation of $v_2$ from final state particle kinematic information and learning the centrality and the transverse momentum...
Article
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The risk of bias in academic publishing is present from the first stages of the publishing process when the author creates an account and submits the manuscript, which becomes subject to the rights and power of journal editors. The author’s disclosure of certain personal information risks exposing him/her to biases for or against certain groups of...
Technical Report
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Since the 19 th century, it has been known that the estimation of the population variance from a sample needs to be corrected to remove bias (Bessel's correction), and that even when the estimation of the variance can be unbiased, the corresponding estimation of the standard deviation is still biased. Unfortunately, the probability distribution of...