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In semi-supervised fuzzy clustering, this paper extends the traditional pairwise constraint (i.e., must-link or cannot-link) to fuzzy pairwise constraint. The fuzzy pairwise constraint allows a supervisor to provide the grade of similarity…

Machine Learning · Computer Science 2021-11-23 Zhen Wang , Shan-Shan Wang , Lan Bai , Wen-Si Wang , Yuan-Hai Shao

With the membership function being strictly positive, the conventional fuzzy c-means clustering method sometimes causes imbalanced influence when clusters of vastly different sizes exist. That is, an outstandingly large cluster drags to its…

Machine Learning · Statistics 2023-03-28 Akira R. Kinjo , Daphne Teck Ching Lai

The framework of Integral Quadratic Constraints (IQC) reduces the computation of upper bounds on the convergence rate of several optimization algorithms to a semi-definite program (SDP). In the case of over-relaxed Alternating Direction…

Machine Learning · Statistics 2018-03-06 Guilherme França , José Bento

It is well-known that by adding integrality constraints to the semidefinite programming (SDP) relaxation of the max-cut problem, the resulting integer semidefinite program is an exact formulation of the problem. In this paper we show…

Optimization and Control · Mathematics 2023-11-09 Frank de Meijer , Renata Sotirov

Quantified Integer Programming (QIP) bridges multiple domains by extending Quantified Boolean Formulas (QBF) to incorporate general integer variables and linear constraints while also generalizing Integer Programming through variable…

Discrete Mathematics · Computer Science 2025-06-06 Michael Hartisch , Leroy Chew

Causal inference in modern largescale systems faces growing challenges, including highdimensional covariates, multi-valued treatments, massive observational (OBS) data, and limited randomized controlled trial (RCT) samples due to cost…

Methodology · Statistics 2026-02-27 Yuxi Du , Zhiheng Zhang , Haoxuan Li , Cong Fang , Jixing Xu , Peng Zhen , Jiecheng Guo

A sequential quadratic programming (SQP) algorithm is designed for nonsmooth optimization problems with upper-C^2 objective functions. Upper-C^2 functions are locally equivalent to difference-of-convex (DC) functions with smooth convex…

Optimization and Control · Mathematics 2023-10-31 Jingyi Wang , Cosmin G. Petra

Many parallel algorithms use at least linear auxiliary space in the size of the input to enable computations to be done independently without conflicts. Unfortunately, this extra space can be prohibitive for memory-limited machines,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-02 Yan Gu , Omar Obeya , Julian Shun

A long-standing issue with deep learning is the need for large and consistently labeled datasets. Although the current research in semi-supervised learning can decrease the required amount of annotated data by a factor of 10 or even more,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Lars Schmarje , Johannes Brünger , Monty Santarossa , Simon-Martin Schröder , Rainer Kiko , Reinhard Koch

With the rapid advancement of large language models (LLMs), natural language processing (NLP) has achieved remarkable progress. Nonetheless, significant challenges remain in handling texts with ambiguity, polysemy, or uncertainty. We…

Computation and Language · Computer Science 2025-09-29 Ping Chen , Xiang Liu , Zhaoxiang Liu , Zezhou Chen , Xingpeng Zhang , Huan Hu , Zipeng Wang , Kai Wang , Shuming Shi , Shiguo Lian

We propose an interior point method (IPM) for solving semidefinite programming problems (SDPs). The standard interior point algorithms used to solve SDPs work in the space of positive semidefinite matrices. Contrary to that the proposed…

Optimization and Control · Mathematics 2023-01-18 Felix Kirschner , Etienne de Klerk

Federated Class Incremental Learning (FCIL) is a new direction in continual learning (CL) for addressing catastrophic forgetting and non-IID data distribution simultaneously. Existing FCIL methods call for high communication costs and…

Due to the unobservability of confoundings, there has been widespread concern about how to compute causality quantitatively. To address this challenge, proxy-based negative control approaches have been commonly adopted, where auxiliary…

Optimization and Control · Mathematics 2022-11-09 Zhiheng Zhang

Fuzzy implication functions are a key area of study in fuzzy logic, extending the classical logical conditional to handle truth degrees in the interval $[0,1]$. While existing literature often focuses on a limited number of families, in the…

Artificial Intelligence · Computer Science 2025-03-11 Raquel Fernandez-Peralta

We study a new class of functions that arise naturally in quaternionic analysis, we call them "quasi regular functions". Like the well-known quaternionic regular functions, these functions provide representations of the quaternionic…

Representation Theory · Mathematics 2026-01-26 Igor Frenkel , Matvei Libine

Natural-language planning often involves vague predicates (e.g., suitable substitute, stable enough) whose satisfaction is inherently graded. Existing category-theoretic planners provide compositional structure and pullback-based…

Artificial Intelligence · Computer Science 2026-01-29 Shuhui Qu

Intuitively, an ideal collaborative filtering (CF) model should learn from users' full rankings over all items to make optimal top-K recommendations. Due to the absence of such full rankings in practice, most CF models rely on pairwise loss…

Information Retrieval · Computer Science 2024-12-25 Yuhan Zhao , Rui Chen , Li Chen , Shuang Zhang , Qilong Han , Hongtao Song

A new message-passing (MP) method is considered for the matrix completion problem associated with recommender systems. We attack the problem using a (generative) factor graph model that is related to a probabilistic low-rank matrix…

Information Theory · Computer Science 2010-07-06 Byung-Hak Kim , Arvind Yedla , Henry D. Pfister

The fuzzy integral is a powerful parametric nonlin-ear function with utility in a wide range of applications, from information fusion to classification, regression, decision making,interpolation, metrics, morphology, and beyond. While the…

Artificial Intelligence · Computer Science 2020-10-22 Derek Anderson , Matthew Deardorff , Timothy Havens , Siva Kakula , Timothy Wilkin , Muhammad Islam , Anthony Pinar , Andrew Buck

Fractional cumulative residual inaccuracy (FCRI) measure allows to determine regions of discrepancy between systems, depending on their respective fractional and chaotic map parameters. Most of the theoretical results and applications…

Applications · Statistics 2025-11-25 Iona Ann Sebastian , S. M. Sunoj