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Journal articles on the topic 'Pseudo-weights'

Author: Grafiati

Published: 4 June 2025

Last updated: 15 July 2025

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1

Zhukovsky, Mikhail O. "Medieval Weights with Pseudo-Arabic Inscriptions." Povolzhskaya Arkheologiya (The Volga River Region Archaeology) 4, no. 26 (2018): 117–36. http://dx.doi.org/10.24852/2018.4.26.117.136.

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2

Gala, Sadek. "Multipliers spaces, Muckenhoupt weights and pseudo-differential operators." Journal of Mathematical Analysis and Applications 324, no. 2 (2006): 1262–73. http://dx.doi.org/10.1016/j.jmaa.2005.12.040.

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3

Kim, Jee In, HyeongSeok Kim, and Jun Lee. "Evaluation of pseudo-haptic interfaces for perceiving virtual weights." International Journal of Data Mining and Bioinformatics 23, no. 1 (2020): 30. http://dx.doi.org/10.1504/ijdmb.2020.10027153.

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Lee, Jun, Jee In Kim, and HyungSeok Kim. "Evaluation of pseudo-haptic interfaces for perceiving virtual weights." International Journal of Data Mining and Bioinformatics 23, no. 1 (2020): 30. http://dx.doi.org/10.1504/ijdmb.2020.105432.

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Cesarano, Clemente, and Paolo Ricci. "Orthogonality Properties of the Pseudo-Chebyshev Functions (Variations on a Chebyshev’s Theme)." Mathematics 7, no. 2 (2019): 180. http://dx.doi.org/10.3390/math7020180.

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The third and fourth pseudo-Chebyshev irrational functions of half-integer degree are defined. Their definitions are connected to those of the first- and second-kind pseudo-Chebyshev functions. Their orthogonality properties are shown, with respect to classical weights.

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Liang, Rong, and Xiaohong Zhang. "Interval-Valued Pseudo Overlap Functions and Application." Axioms 11, no. 5 (2022): 216. http://dx.doi.org/10.3390/axioms11050216.

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A class of interval-valued OWA operators can be constructed from interval-valued overlap functions with interval-valued weights, which plays an important role in solving multi-attribute decision making (MADM) problems considering interval numbers as attribute values. Among them, when the importance of multiple attributes is different, it can only be calculated by changing the interval-valued weights. In fact, we can directly abandon the commutativity and extend the interval-valued overlap functions (IO) to interval-valued pseudo overlap functions (IPO) so that function itself implies the weigh

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WANG, Chong. "The Weighted Embedded Homology of Super-Hypergraphs." Wuhan University Journal of Natural Sciences 29, no. 6 (2024): 523–28. https://doi.org/10.1051/wujns/2024296523.

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In this paper, we deﬁne the weighted embedded homology of super-hypergraphs, give a quasi-partial order and a pseudo-metric on the set made up of all non-vanishing weights on a ﬁnite set, and clarify the relationship between the torsion parts of weighted embedded homology with integer coeﬃcients of super-hypergraphs under certain weights.

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Qian, Feng, Juan Yang, Sipeng Tang, Gao Chen, and Jingwen Yan. "Addressing Noisy Pixels in Weakly Supervised Semantic Segmentation with Weights Assigned." Mathematics 12, no. 16 (2024): 2520. http://dx.doi.org/10.3390/math12162520.

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Weakly supervised semantic segmentation (WSSS) aims to segment objects without a heavy burden of dense annotations. Pseudo-masks serve as supervisory information for training segmentation models, which is crucial to the performance of segmentation models. However, the generated pseudo-masks contain significant noisy labels, which leads to poor performance of the segmentation models trained on these pseudo-masks. Few studies address this issue, as these noisy labels remain inevitable even after the pseudo-masks are improved. In this paper, we propose an uncertainty-weight transform module to mi

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Fernstål, Lotta. "A Bit Arabic: Pseudo-Arabic Inscriptions on Viking Age Weights in Sweden and Expressions of Self-image." Current Swedish Archaeology 16, no. 1 (2021): 61–71. http://dx.doi.org/10.37718/csa.2008.04.

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There are many Viking Age weights in Scandinavia, and not least in Swedcn. A few of the sphrrical weights with flat poles, which were used for weighing silver in trading situations, display so-called pseudo-Arabic inscriptions, i.e. writing which resembles Arabic but which is mostly illegible. Why did some people put Arabic-like writing on their weights, and what did they hope to achieve by this? These questions are discussed together with positive aspects of trade, interaction and encounters with foreigners, visual aspects of weights and weighing, as well as personal choices in the presentati

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Charalampous, Periklis, Carolien C. H. M. Maas, and Juanita A. Haagsma. "Disability weights for environmental noise-related health states: results of a disability weights measurement study in Europe." BMJ Public Health 2, no. 1 (2024): e000470. http://dx.doi.org/10.1136/bmjph-2023-000470.

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IntroductionMeasurement of the burden of disease using disability-adjusted life years requires disability weights to quantify health losses for non-fatal consequences of disease and injury. We aimed to obtain a set of disability weights for environmental and non-environmental noise-related health states (NOISE) using a nationally representative sample survey among the general population of four European countries; and to compare the resulting NOISE disability weights with those estimated in the Global Burden of Disease 2010 (GBD 2010) and European (EURO) disability weights measurement studies.

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11

Elliott, Michael R. "Combining Data from Probability and Non- Probability Samples Using Pseudo-Weights." Survey Practice 2, no. 6 (2009): 1–7. http://dx.doi.org/10.29115/sp-2009-0025.

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12

Pan, Guocheng. "Extended weights of evidence modeling for the pseudo-estimation of metal grades." Nonrenewable Resources 5, no. 1 (1996): 53–76. http://dx.doi.org/10.1007/bf02259070.

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13

Yang, Lingli, Balgobin Nandram, and Jai Won Choi. "Bayesian Predictive Inference Under Nine Methods for Incorporating Survey Weights." International Journal of Statistics and Probability 12, no. 1 (2023): 33. http://dx.doi.org/10.5539/ijsp.v12n1p33.

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Sample surveys play a significant role in obtaining reliable estimators of finite population quantities, and survey weights are used to deal with selection bias and&nbsp; non-response bias. The main idea of this research is to compare the performance of nine methods with differently constructed survey weights, and we can use these methods for non-probability sampling after weights are estimated (e.g. quasi-randomization). The original survey weights are calibrated to the population size. In particular, the base model does not include survey weights or design weights. We use original survey

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14

Zhao, Xinqiao, Feilong Tang, Xiaoyang Wang, and Jimin Xiao. "SFC: Shared Feature Calibration in Weakly Supervised Semantic Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 7 (2024): 7525–33. http://dx.doi.org/10.1609/aaai.v38i7.28584.

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Image-level weakly supervised semantic segmentation has received increasing attention due to its low annotation cost. Existing methods mainly rely on Class Activation Mapping (CAM) to obtain pseudo-labels for training semantic segmentation models. In this work, we are the first to demonstrate that long-tailed distribution in training data can cause the CAM calculated through classifier weights over-activated for head classes and under-activated for tail classes due to the shared features among head- and tail- classes. This degrades pseudo-label quality and further influences final semantic seg

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Yoo, Young jun, Dae sung Jung, Yu jin Jang, and Sang chul Won. "Fuzzy weighted subtask controller for redundant manipulator." Robotica 33, no. 2 (2014): 295–313. http://dx.doi.org/10.1017/s0263574714000344.

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SUMMARYWe propose a fuzzy weighted subtask controller for a redundant robot manipulator. To expand the feasibility of the inverse kinematic solution, we introduce a weighted pseudo-inverse that changes the null-space of the Jacobian. The weights of elements in the pseudo-inverse are obtained using fuzzy rules that are related to the null-space velocity tracking error. With the pseudo-inverse, we develop a task space controller to track a desired task space trajectory and subtask control input. We propose a weighted subtask controller for multiple subtasks. The results of a simulation and exper

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DING, HENG-TONG, ANDREA DAINESE, ZAIDA CONESA DEL VALLE, and DAICUI ZHOU. "STUDYING THE ENERGY LOSS OF HEAVY QUARKS VIA SINGLE MUON PRODUCTION IN PbPb COLLISIONS AT $\sqrt{^SNN} = 5.5 {\rm TeV}$." International Journal of Modern Physics E 16, no. 07n08 (2007): 2041–47. http://dx.doi.org/10.1142/s021830130700743x.

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The effects of heavy quarks energy loss on the transverse momentum spectra of single muons are studied. The energy loss of heavy quarks when traversing the medium formed in PbPb collisions at [Formula: see text] is calculated by implementing the collision geometry and the quenching weights. The medium density is assumed to decrease at forward pseudo-rapidity and to be proportional with pseudo-rapidity multiplicity dN/dη. Muons from W decays can be used as a medium-blind reference to quantify the effect of heavy quarks energy loss on the single muon production.

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17

Wulan, Hasi, and Kehe Zhu. "Lipschitz Type Characterizations for Bergman Spaces." Canadian Mathematical Bulletin 52, no. 4 (2009): 613–26. http://dx.doi.org/10.4153/cmb-2009-060-6.

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AbstractWe obtain new characterizations for Bergman spaces with standard weights in terms of Lipschitz type conditions in the Euclidean, hyperbolic, and pseudo-hyperbolic metrics. As a consequence, we prove optimal embedding theorems when an analytic function on the unit disk is symmetrically lifted to the bidisk.

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18

You, Yong, and J. N. K. Rao. "Pseudo hierarchical Bayes small area estimation combining unit level models and survey weights." Journal of Statistical Planning and Inference 111, no. 1-2 (2003): 197–208. http://dx.doi.org/10.1016/s0378-3758(02)00301-4.

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TOGAWA, NOZOMU, KAORU UKAI, MASAO YANAGISAWA, and TATSUO OHTSUKI. "A SIMULTANEOUS PLACEMENT AND GLOBAL ROUTING ALGORITHM FOR FPGAS WITH POWER OPTIMIZATION." Journal of Circuits, Systems and Computers 09, no. 01n02 (1999): 99–112. http://dx.doi.org/10.1142/s0218126699000098.

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This paper proposes a simultaneous placement and global routing algorithm for FPGAs with power optimization. The algorithm is based on hierarchical bipartitioning of layout regions and sets of logic-blocks. When bipartitioning a layout region, pseudo-blocks are introduced to preserve connections if there exist connections between bipartitioned logic-block sets. A global route is represented by a sequence of pseudo-blocks. Since pseudo-blocks and logic-blocks can be dealt with equally, placement and global routing are processed simultaneously. The algorithm gives weights to nets with high switc

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Li, Boliang, Yaming Xu, Yan Wang, Luxiu Li, and Bo Zhang. "The student-teacher framework guided by self-training and consistency regularization for semi-supervised medical image segmentation." PLOS ONE 19, no. 4 (2024): e0300039. http://dx.doi.org/10.1371/journal.pone.0300039.

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Due to the high suitability of semi-supervised learning for medical image segmentation, a plethora of valuable research has been conducted and has achieved noteworthy success in this field. However, many approaches tend to confine their focus to a singular semi-supervised framework, thereby overlooking the potential enhancements in segmentation performance offered by integrating several frameworks. In this paper, we propose a novel semi-supervised framework named Pesudo-Label Mean Teacher (PLMT), which synergizes the self-training pipeline with pseudo-labeling and consistency regularization te

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ROJAS, I., J. GONZALEZ, A. CAÑAS, A. F. DIAZ, F. J. ROJAS, and M. RODRIGUEZ. "SHORT-TERM PREDICTION OF CHAOTIC TIME SERIES BY USING RBF NETWORK WITH REGRESSION WEIGHTS." International Journal of Neural Systems 10, no. 05 (2000): 353–64. http://dx.doi.org/10.1142/s0129065700000351.

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We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters σ are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibility with respect to function approximation. We propose a modified PG-BF (pseudo-gaussian basis function) network in which the regression weights are used to replace the constant weights in the output layer. For this purpose, a sequential learning algori

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22

Qiu, Yang, Hande Dong, Jiawei Chen, and Xiangnan He. "LightAD: Accelerating AutoDebias with Adaptive Sampling." JUSTC 53 (2023): 1. http://dx.doi.org/10.52396/justc-2022-0100.

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In recommendation systems, the bias issue is ubiquitous as the data is collected from user behaviors rather than reasonable experiments. AutoDebias, which resorts to meta learning to find appropriate debiasing configurations, <i>i.e.</i>, pseudo-labels and confidence weights for all user-item pairs, has been demonstrated as a generic and effective solution in tackling various biases. Nevertheless, setting pseudo-labels and weights for every user-item pair can be a time-consuming process. Therefore, AutoDebias suffers from a huge computational cost, making it less applicable to real

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Montesinos-López, Osval A., Kent Eskridge, Abelardo Montesinos-López, José Crossa, Moises Cortés-Cruz, and Dong Wang. "A regression model for pooled data in a two-stage survey under informative sampling with application for detecting and estimating the presence of transgenic corn." Seed Science Research 26, no. 2 (2016): 182–97. http://dx.doi.org/10.1017/s0960258516000015.

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AbstractGroup-testing regression methods are effective for estimating and classifying binary responses and can substantially reduce the number of required diagnostic tests. However, there is no appropriate methodology when the sampling process is complex and informative. In these cases, researchers often ignore stratification and weights that can severely bias the estimates of the population parameters. In this paper, we develop group-testing regression models for analysing two-stage surveys with unequal selection probabilities and informative sampling. Weights are incorporated into the likeli

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Lee, Chan, Seungho Shin, Gyeong-Moon Park, and Jung Uk Kim. "Multispectral Pedestrian Detection with Sparsely Annotated Label." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 4 (2025): 4482–90. https://doi.org/10.1609/aaai.v39i4.32472.

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Although existing Sparsely Annotated Object Detection (SAOD) approches have made progress in handling sparsely annotated environments in multispectral domain, where only some pedestrians are annotated, they still have the following limitations: (i) they lack considerations for improving the quality of pseudo-labels for missing annotations, and (ii) they rely on fixed ground truth annotations, which leads to learning only a limited range of pedestrian visual appearances in the multispectral domain. To address these issues, we propose a novel framework called Sparsely Annotated Multispectral Ped

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Ma, Jiang, Wei Zhao, Yanguo Jia, and Haiyang Jiang. "New Generalized Cyclotomic Quaternary Sequences with Large Linear Complexity and a Product of Two Primes Period." Information 12, no. 5 (2021): 193. http://dx.doi.org/10.3390/info12050193.

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Linear complexity is an important criterion to characterize the unpredictability of pseudo-random sequences, and large linear complexity corresponds to high cryptographic strength. Pseudo-random Sequences with a large linear complexity property are of importance in many domains. In this paper, based on the theory of inverse Gray mapping, two classes of new generalized cyclotomic quaternary sequences with period pq are constructed, where pq is a product of two large distinct primes. In addition, we give the linear complexity over the residue class ring Z4 via the Hamming weights of their Fourie

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Bartlett, Peter L., Vitaly Maiorov, and Ron Meir. "Almost Linear VC-Dimension Bounds for Piecewise Polynomial Networks." Neural Computation 10, no. 8 (1998): 2159–73. http://dx.doi.org/10.1162/089976698300017016.

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We compute upper and lower bounds on the VC dimension and pseudodimension of feedforward neural networks composed of piecewise polynomial activation functions. We show that if the number of layers is fixed, then the VC dimension and pseudo-dimension grow as W log W, where W is the number of parameters in the network. This result stands in opposition to the case where the number of layers is unbounded, in which case the VC dimension and pseudo-dimension grow as W2. We combine our results with recently established approximation error rates and determine error bounds for the problem of regression

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HUC, FLORIAN, CLÁUDIA LINHARES SALES, and HERVÉ RIVANO. "THE PROPORTIONAL COLORING PROBLEM: OPTIMIZING BUFFERS IN RADIO MESH NETWORKS." Discrete Mathematics, Algorithms and Applications 04, no. 03 (2012): 1250028. http://dx.doi.org/10.1142/s1793830912500280.

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In this paper, we consider a new edge coloring problem to model call scheduling optimization issues in wireless mesh networks: the proportional coloring. It consists in finding a minimum cost edge coloring of a graph which preserves the proportion given by the weights associated to each of its edges. We show that deciding if a weighted graph admits a proportional coloring is pseudo-polynomial while determining its proportional chromatic index is NP-hard. We then give lower and upper bounds for this parameter that can be computed in pseudo-polynomial time. We finally identify a class of graphs

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Abdeljawad, Ahmed, Sandro Coriasco, and Joachim Toft. "Liftings for ultra-modulation spaces, and one-parameter groups of Gevrey-type pseudo-differential operators." Analysis and Applications 18, no. 04 (2019): 523–83. http://dx.doi.org/10.1142/s0219530519500143.

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We deduce one-parameter group properties for pseudo-differential operators [Formula: see text], where [Formula: see text] belongs to the class [Formula: see text] of certain Gevrey symbols. We use this to show that there are pseudo-differential operators [Formula: see text] and [Formula: see text] which are inverses to each other, where [Formula: see text] and [Formula: see text]. We apply these results to deduce lifting property for modulation spaces and construct explicit isomorphisms between them. For each weight functions [Formula: see text] moderated by GRS submultiplicative weights, we p

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Li, Wende, Jianlong Chen, Yukun Zhou, and Xiaofeng Chen. "Weighted generalized invertibility in two semigroups of a ring with involution." Filomat 38, no. 15 (2024): 5261–74. https://doi.org/10.2298/fil2415261l.

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Let R be a ring with an involution and p ? R be a weighted projection. We characterize the relation between the weighted Moore-Penrose invertibility (resp., weighted pseudo core invertibility) of the corresponding elements of the two semigroups pRp and pRp + 1-p. As an application, we obtain the relation between the weighted Moore-Penrose invertibility (resp., weighted pseudo core invertibility) of the corresponding elements of the matrix semigroup AA? M,N Rm?m AA?M,N + Im-AA?M,N and the matrix semigroup A?M,N ARn?n A?M,N A + In-A?M,N A, where A ? Rm?n be weighted Moore-Penrose invertible with

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Zhang, Quan, Yuxin Qi, Xi Tang, et al. "Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 10 (2025): 10085–93. https://doi.org/10.1609/aaai.v39i10.33094.

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Pseudo-label learning methods have been widely applied in weakly-supervised temporal action localization. Existing works directly utilize weakly-supervised base model to generate instance-level pseudo-labels for training the fully-supervised detection head. We argue that the noise in pseudo-labels would interfere with the learning of fully-supervised detection head, leading to significant performance leakage. Issues with noisy labels include:(1) inaccurate boundary localization; (2) undetected short action clips; (3) multiple adjacent segments incorrectly detected as one segment. To target the

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Chen, Hao, Zhuoyang Zou, and Xinghui Zhu. "Proxy-Based Semi-Supervised Cross-Modal Hashing." Applied Sciences 15, no. 5 (2025): 2390. https://doi.org/10.3390/app15052390.

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Due to the difficulty in obtaining label information in practical applications, semi-supervised cross-modal retrieval has emerged. However, the existing semi-supervised cross-modal hashing retrieval methods mainly focus on exploring the structural relationships between data and generating high-quality discrete pseudo-labels while neglecting the relationships between data and categories, as well as the structural relationships between data and categories inherent in continuous pseudo-labels. Based on this, Proxy-based Semi-Supervised Cross-Modal Hashing (PSSCH) is proposed. Specifically, we pro

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Zhang, Xinzheng, Jinlin Li, Chao Li, and Guojin Liu. "Multi-Teacher D-S Fusion for Semi-Supervised SAR Ship Detection." Remote Sensing 16, no. 15 (2024): 2759. http://dx.doi.org/10.3390/rs16152759.

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Ship detection from synthetic aperture radar (SAR) imagery is crucial for various fields in real-world applications. Numerous deep learning-based detectors have been investigated for SAR ship detection, which requires a substantial amount of labeled data for training. However, SAR data annotation is time-consuming and demands specialized expertise, resulting in deep learning-based SAR ship detectors struggling due to a lack of annotations. With limited labeled data, semi-supervised learning is a popular approach for boosting detection performance by excavating valuable information from unlabel

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Zhang, Xinliang, Lei Zhu, Hangzhou He, Lujia Jin, and Yanye Lu. "Scribble Hides Class: Promoting Scribble-Based Weakly-Supervised Semantic Segmentation with Its Class Label." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 7 (2024): 7332–40. http://dx.doi.org/10.1609/aaai.v38i7.28563.

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Scribble-based weakly-supervised semantic segmentation using sparse scribble supervision is gaining traction as it reduces annotation costs when compared to fully annotated alternatives. Existing methods primarily generate pseudo-labels by diffusing labeled pixels to unlabeled ones with local cues for supervision. However, this diffusion process fails to exploit global semantics and class-specific cues, which are important for semantic segmentation. In this study, we propose a class-driven scribble promotion network, which utilizes both scribble annotations and pseudo-labels informed by image-

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Huang, Xin, Rongwu Xu, and Ruibiao Li. "A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning." Journal of Marine Science and Engineering 13, no. 7 (2025): 1303. https://doi.org/10.3390/jmse13071303.

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Accurate prediction of ship underwater radiated noise (URN) during navigation is critical for evaluating acoustic stealth performance and analyzing detection risks. However, the labeled data available for the training of URN prediction model is limited. Semi-supervised learning (SSL) can improve the model performance by using unlabeled data in the case of a lack of labeled data. Therefore, this paper proposes an SSL method for URN prediction. First, an anti-perturbation regularization is constructed using unlabeled data to optimize the objective function of EL, which is then used in the Geneti

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Graupe, D., and H. Kordylewski. "A Large Memory Storage and Retrieval Neural Network for Adaptive Retrieval and Diagnosis." International Journal of Software Engineering and Knowledge Engineering 08, no. 01 (1998): 115–38. http://dx.doi.org/10.1142/s0218194098000091.

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The neural network discussed in this paper is a self trained network for LArge Memory STorage And Retrieval (LAMSTAR) of information. It employs features such as forgetting, interpolation, extrapolation and filtering, to enhance processing and memory efficiency and to allow zooming in and out of memories. The network is based on modified SOM (Self-Organizing-Map) modules and on arrays of link-weight vectors to channel information vertically and horizontally throughout the network. Direct feedback and up/down counting serve to set these link weights as a higher-hierarchy performance evaluator e

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Huriaty, Dina, and Djemari Mardapi. "AKURASI METODE KALIBRASI FIXED PARAMETER: STUDI PADA PERANGKAT UJIAN NASIONAL MATA PELAJARAN MATEMATIKA." Jurnal Penelitian dan Evaluasi Pendidikan 18, no. 2 (2014): 188–201. http://dx.doi.org/10.21831/pep.v18i2.2860.

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Penelitian ini bertujuan untuk (1) mengidentifikasi karakteristik butir-butir tes pada perangkat soal ujian nasional mata pelajaran Matematika tingkat SMP tahun pelajaran 2009/2010 yang dikalibrasi dengan metode kalibrasi fixed parameter, dan (2) mengetahui metode kalibrasi fixed parameter yang paling akurat di antara metode NWU-OEM (no prior weights updating and one expectation-maximization cycle), NWU-MEM (no prior weights updating and multiple expectation-maximization cycles), OWU-OEM (one prior weights updating and one expectation-maximization cycle), OWU-MEM (one prior weights updating an

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You, Yong, and J. N. K. Rao. "A pseudo-empirical best linear unbiased prediction approach to small area estimation using survey weights." Canadian Journal of Statistics 30, no. 3 (2002): 431–39. http://dx.doi.org/10.2307/3316146.

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Rafei, Ali, Carol A. C. Flannagan, and Michael R. Elliott. "Big Data for Finite Population Inference: Applying Quasi-Random Approaches to Naturalistic Driving Data Using Bayesian Additive Regression Trees." Journal of Survey Statistics and Methodology 8, no. 1 (2020): 148–80. http://dx.doi.org/10.1093/jssam/smz060.

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Abstract Big Data are a “big challenge” for finite population inference. Lack of control over data-generating processes by researchers in the absence of a known random selection mechanism may lead to biased estimates. Further, larger sample sizes increase the relative contribution of selection bias to squared or absolute error. One approach to mitigate this issue is to treat Big Data as a random sample and estimate the pseudo-inclusion probabilities through a benchmark survey with a set of relevant auxiliary variables common to the Big Data. Since the true propensity model is usually unknown,

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Mittlböck, Martina, Ulrike Pötschger, and Harald Heinzl. "Weighted pseudo-values for partly unobserved group membership in paediatric stem cell transplantation studies." Statistical Methods in Medical Research 31, no. 1 (2021): 76–86. http://dx.doi.org/10.1177/09622802211041756.

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Generalised pseudo-values have been suggested to evaluate the impact of allogeneic stem cell transplantation on childhood leukaemia. The approach compares long-term survival of two cohorts defined by the availability or non-availability of suitable donors for stem cell transplantation. A patient's cohort membership becomes known only after completed donor search with or without an identified donor. If a patient suffers an event during donor search, stem cell transplantation will no longer be indicated. In such a case, donor search will be ceased and cohort membership will remain unknown. The g

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Savitsky, Terrance D., and Matthew R. Williams. "Pseudo Bayesian Mixed Models under Informative Sampling." Journal of Official Statistics 38, no. 3 (2022): 901–28. http://dx.doi.org/10.2478/jos-2022-0039.

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Abstract When random effects are correlated with survey sample design variables, the usual approach of employing individual survey weights (constructed to be inversely proportional to the unit survey inclusion probabilities) to form a pseudo-likelihood no longer produces asymptotically unbiased inference. We construct a weight-exponentiated formulation for the random effects distribution that achieves approximately unbiased inference for generating hyperparameters of the random effects. We contrast our approach with frequentist methods that rely on numerical integration to reveal that the pseu

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Kim, Jae Kwang, and Kosuke Morikawa. "An Empirical Likelihood Approach to Reduce Selection Bias in Voluntary Samples." Calcutta Statistical Association Bulletin 75, no. 1 (2023): 8–27. http://dx.doi.org/10.1177/00080683231186488.

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How to construct the pseudo-weights in voluntary samples is an important practical problem in survey sampling. The problem is quite challenging when the sampling mechanism for the voluntary sample is allowed to be non-ignorable. Under the assumption that the sample participation model is correctly specified, we can compute a consistent estimator of the model parameter and construct the propensity score estimator of the population mean. We propose using the empirical likelihood method to construct the final weights for voluntary samples by incorporating the bias calibration constraints and the

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Guo, Hua, Jikui Wang, Wei Ao, and Yulin He. "SGB-ELM: An Advanced Stochastic Gradient Boosting-Based Ensemble Scheme for Extreme Learning Machine." Computational Intelligence and Neuroscience 2018 (June 26, 2018): 1–14. http://dx.doi.org/10.1155/2018/4058403.

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A novel ensemble scheme for extreme learning machine (ELM), named Stochastic Gradient Boosting-based Extreme Learning Machine (SGB-ELM), is proposed in this paper. Instead of incorporating the stochastic gradient boosting method into ELM ensemble procedure primitively, SGB-ELM constructs a sequence of weak ELMs where each individual ELM is trained additively by optimizing the regularized objective. Specifically, we design an objective function based on the boosting mechanism where a regularization item is introduced simultaneously to alleviate overfitting. Then the derivation formula aimed at

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Safari, Maryam, Itziar Otaegi, Nora Aramburu, et al. "Synthesis, Structure, Crystallization and Mechanical Properties of Isodimorphic PBS-ran-PCL Copolyesters." Polymers 13, no. 14 (2021): 2263. http://dx.doi.org/10.3390/polym13142263.

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Isodimorphic behavior is determined by partial inclusion of comonomer segments within the crystalline structure and arises from the comparatively similar repeating chain units of the parental homopolymers. Isodimorphic random copolymers are able to crystallize irrespective of their composition and exhibit a pseudo-eutectic behavior when their melting point values are plotted as a function of comonomer content. At the pseudo-eutectic point or region, two crystalline phases can coexist. On the right-hand and the left-hand side of the pseudo-eutectic point or region, only one single crystalline p

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Zhou, Jiaying, Yang Liu, and Qingchao Chen. "Novel Class Discovery in Chest X-rays via Paired Images and Text." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 7 (2024): 7650–58. http://dx.doi.org/10.1609/aaai.v38i7.28598.

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Novel class discover(NCD) aims to identify new classes undefined during model training phase with the help of knowledge of known classes. Many methods have been proposed and notably boosted performance of NCD in natural images. However, there has been no work done in discovering new classes based on medical images and disease categories, which is crucial for understanding and diagnosing specific diseases. Moreover, most of the existing methods only utilize information from image modality and use labels as the only supervisory information. In this paper, we propose a multi-modal novel class dis

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Chang, Der-Chen, and Bao Qin Li. "Sobolev and Lipschitz estimates for weighted Bergman projections." Nagoya Mathematical Journal 147 (September 1997): 147–78. http://dx.doi.org/10.1017/s002776300000636x.

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AbstractLet Ω be a bounded, decoupled pseudo-convex domain of finite type in ℂn with smooth boundary. In this paper, we generalize results of Bonami-Grellier [BG] and Bonami-Chang-Grellier [BCG] to study weighted Bergman projections for weights which are a power of the distance to the boundary. We define a class of operators of Bergman type for which we develop a functional calculus. Then we may obtain Sobolev and Lipschitz estimates, both of isotropic and anisotropic type, for these projections.

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Lee, Jun, Younggwang Lee, and Sungjun Park. "Virtual Gymnasium: Personalized Weight Perception Interface in Lifting Virtual Objects." Applied Sciences 12, no. 23 (2022): 12414. http://dx.doi.org/10.3390/app122312414.

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This paper proposes a pseudo-haptic interface that depicts the virtual weights of dumbbells in a virtual gymnasium. When a user performs a dumbbell biceps curl, he/she fixes the elbow joint as a standard joint and lifts the dumbbell, with its movement trajectory represented as a circular arc. The trajectories and velocity of dumbbell bicep curls differ depending on human physiological characteristics. Therefore, the proposed system provides an adaptable exercise area and force visualization of virtual dumbbells using a velocity-based pseudo-haptic interface and computer vision-based tracking m

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Chen, Junchi, Richong Zhang, and Junfan Chen. "Semi-Supervised Multimodal Classification Through Learning from Modal and Strategic Complementarities." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 15 (2025): 15812–20. https://doi.org/10.1609/aaai.v39i15.33736.

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Supervised multimodal classification has been proven to outperform unimodal classification in the image-text domain. However, this task is highly dependent on abundant labeled data. To perform multimodal classification in data-insufficient scenarios, in this study, we explore semi-supervised multimodal classification (SSMC) that only requires a small amount of labeled data and plenty of unlabeled data. Specifically, we first design baseline SSMC models by combining known semi supervised pseudo-labeling methods with the two most commonly used modal fusion strategies, i.e. feature-level fusion a

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Akhirjulima, Rinzan, IGBN Makertihartha, Tri Partono Adhi, and Anggit Raksajati. "IMPROVING HYDROCARBON RESIDUE FEED DEFINITION THROUGH VALIDATED SIMULATION MODELS." Scientific Contributions Oil and Gas 48, no. 1 (2025): 1–10. https://doi.org/10.29017/scog.v48i1.1683.

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The conventional development of deasphalting processes relies on costly and time-consuming lab experiments. This study introduces a more efficient approach using simulation to tackle these challenges. The method identifies the composition of synthetic crude oil (SCO) feedstock, dividing it into four key molecular groups: Saturates, Aromatics, Resins, and Asphaltenes (SARA). These groups are pseudo-components in the simulation, characterized by parameters like boiling points and molecular weights. The simulated boiling points are then compared with actual crude oil to ensure accuracy. The frame

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Zhu, Pengfei, Qian Wang, Yu Wang, Jialu Li, and Qinghua Hu. "Every Node Is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 15 (2024): 17184–92. http://dx.doi.org/10.1609/aaai.v38i15.29664.

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Attributed graph clustering is an unsupervised task that partitions nodes into different groups. Self-supervised learning (SSL) shows great potential in handling this task, and some recent studies simultaneously learn multiple SSL tasks to further boost performance. Currently, different SSL tasks are assigned the same set of weights for all graph nodes. However, we observe that some graph nodes whose neighbors are in different groups require significantly different emphases on SSL tasks. In this paper, we propose to dynamically learn the weights of SSL tasks for different nodes and fuse the em

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Park, Suho, SuBeen Lee, Hyun Seok Seong, Jaejoon Yoo, and Jae-Pil Heo. "Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 6 (2025): 6425–33. https://doi.org/10.1609/aaai.v39i6.32688.

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We propose Foreground-Covering Prototype Generation and Matching to resolve Few-Shot Segmentation (FSS), which aims to segment target regions in unlabeled query images based on labeled support images. Unlike previous research, which typically estimates target regions in the query using support prototypes and query pixels, we utilize the relationship between support and query prototypes. To achieve this, we utilize two complementary features: SAM Image Encoder features for pixel aggregation and ResNet features for class consistency. Specifically, we construct support and query prototypes with S

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