TransINT embeds KGs by preserving implication rules, outperforming existing methods.
arXiv research
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Method learns relational features for Gaifman models from knowledge bases.
Study ruled surfaces with finite multiplicity, focusing on their curves and singularities.
R2N learns interpretable rules and literals from numerical features.
In this paper, we consider non developable ruled surface with spacelike ruling, timelike ruling, respectively. We give the relations between the structure functions with the curvature and torsion of the striction line of the timelike and spacelike non developable ruled surfaces. Also, we have calculated the gaussian an…
In this study, we introduce Darboux slant ruled surfaces in the Euclidean 3-space which is defined by the property that the Darboux vector of orthonormel frame of ruled surface makes a constant angle with a fixed, non-zero direction. We obtain the characterizations of Darboux slant ruled surfaces regarding the conical …
We provide self-contained proof of a theorem relating probabilistic coherence of forecasts to their non-domination by rival forecasts with respect to any proper scoring rule. The theorem appears to be new but is closely related to results achieved by other investigators.
A method for learning transition models in uncertain domains using relational rules and neural networks.
In this article supervised learning problems are solved using soft rule ensembles. We first review the importance sampling learning ensembles (ISLE) approach that is useful for generating hard rules. The soft rules are then obtained with logistic regression from the corresponding hard rules. In order to deal with the p…
The paper explores new rules for analyzing label rankings and pairwise preferences.
In this paper, we obtain the characterizations of Mannheim offsets of the timelike ruled surface with spacelike rulings in dual Lorentzian space. We give the relations between terms of their integral invariants and also we give the new characterization of the Mannheim offsets of developable timelike ruled surface. More…
We study ruled surfaces in R3 which are obtained from dual spher- ical indicatrix curves of dual Frenet vector fields. We find the Gaussian and mean curvatures of the ruled surfaces and give some results of being Wein- garten surface.
The Lamarle Formula, given by Kruppa in \cite{Kr}, is known as a relationship between the Gaussian curvature and the distribution parameter of a ruled surface in the surface theory. The ruled surfaces were investigated in 3 different classes with respect to the character of base curves and rulings, \cite{Tu1},\cite{Tu2…
Defines new ruled surfaces using alternative frames and analyzes their geometric properties.
In this paper, we investigate the ruled surfaces generated by a straight line according to rotation minimizing frame (RMF). Using this frame of a straight line, we obtained the necessary and sufficient conditions when the ruled surface is developable. Also, we give some new results and theorems related to be the asympt…
Study on Kähler metrics on ruled surfaces, proving existence and non-existence.
New scoring rule predicts causal relations from data with selection bias.
In this paper, we investigate the relations between the pitch, the angle of pitch and drall of parallel ruled surface of a closed curve in dual Lorentzian space.
We discuss theoretical aspects of the product rule for classification problems in supervised machine learning for the case of combining classifiers. We show that (1) the product rule arises from the MAP classifier supposing equivalent priors and conditional independence given a class; (2) under some conditions, the pro…
New type of ruled surfaces studied with properties and examples.
We consider rules for discarding predictors in lasso regression and related problems, for computational efficiency. El Ghaoui et al (2010) propose "SAFE" rules that guarantee that a coefficient will be zero in the solution, based on the inner products of each predictor with the outcome. In this paper we propose strong …
We strengthen the link between holomorphic and generating-function invariants of Legendrian knots by establishing a formula relating the number of augmentations of a knot's contact homology to the complete ruling invariant of Chekanov and Pushkar.
Enhances visual explanations with logical rules for complex concepts.
Lifted Relational Neural Networks (LRNNs) describe relational domains using weighted first-order rules which act as templates for constructing feed-forward neural networks. While previous work has shown that using LRNNs can lead to state-of-the-art results in various ILP tasks, these results depended on hand-crafted ru…
In this paper, we investigate the relations between the pitch, the angle of pitch and drall of parallel ruled surface of a closed spacelike curve with timelike binormal in dual Lorentzian space.
Understanding the behavior of a trained network and finding explanations for its outputs is important for improving the network's performance and generalization ability, and for ensuring trust in automated systems. Several approaches have previously been proposed to identify and visualize the most important features by…
In this paper, we investigate the relations between the pitch, the angle of pitch and drall of parallel ruled surface of a closed spacelike curve with a spacelike binormal in dual Lorentzian space.
Defines and analyzes generalized normal ruled surfaces of curves in 3D space.
We consider ruled and quadric surfaces in the 3-dimensional Euclidean space which are of coordinate finite type with respect to the third fundamental form , i.e., their position vector satisfies the relation where is a square matrix o…
New algebraic rules for 5D shapes based on 3D cocycles.
DRUM discovers interpretable rules from knowledge graphs for unseen entities.
This paper proposes a framework to learn explainable rules from knowledge graphs for better recommendation.
The aim of this paper is to present a new perspective on the generation of developable trajectory ruled surfaces in Minkowski 3-space. Involute trajectory ruled surfaces generated by the Frenet trihedron, moving along spacelike involutes of a given timelike space curve, is stated according to Lorentzian timelike angle …
Superposition rules form a class of functions that describe general solutions of systems of first-order ordinary differential equations in terms of generic families of particular solutions and certain constants. In this work we extend this notion and other related ones to systems of higher-order differential equations …
We further study the incidence relations that arise from the various subtowers, known as Baby Monster, which exist within the -Monster Tower. This allows us to complete the class spelling rules. We also present a method of calculating the various Baby Monster that appear within the Monster Tower.
SRF learns sparse rule models by screening out features efficiently.
Advocates rule-based approach for multi-label classification.
Mining relationships between treatment(s) and medical problem(s) is vital in the biomedical domain. This helps in various applications, such as decision support system, safety surveillance, and new treatment discovery. We propose a deep learning approach that utilizes both word level and sentence-level representations …
Paper explores subdifferential chain rules for matrix factorization and related machine learning models.
The paper develops methods to derive mixed superposition rules for Lie systems and applies them to various physical systems.
Proposes NLRL for enhancing neural networks' interpretability.
A new gradient boosting method improves interpretability of probabilistic models.
NMLNs use neural networks to learn relational structure from data.
GraIL predicts relations by reasoning over subgraphs, outperforming embeddings.
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps (ESOM) and…
MPNPs use message passing to exploit relational structure in stochastic processes.
New characterizations of ruled real hypersurfaces in complex projective space found.
We consider a skew ruled surface in the Euclidean space and relative normalizations of it, so that the relative normals at each point lie in the corresponding asymptotic plane of . We call such relative normalizations and the resulting relative images of \emph{asymptotic}. We determine all ruled surf…