arXiv research

The paper explores new rules for analyzing label rankings and pairwise preferences.

LoRMIkA finds k-optimal association rules for local model interpretability.

Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for association rules. However, these measures fail to take the probabilistic properties of the mined data into account. In this paper, we start …

Study Legendrian graph invariants via augmentation and ruling polynomials.

Study uses logistic regression and association rules to identify early symptoms of malignant mesothelioma.

This paper deals with the binary classification task when the target class has the lower probability of occurrence. In such situation, it is not possible to build a powerful classifier by using standard methods such as logistic regression, classification tree, discriminant analysis, etc. To overcome this short-coming o…

Invariant Causal Set Covering Machines avoid spurious associations.

We study some properties of decomposable exact Lagrangian cobordisms between Legendrian links in $\mathbb{R}^3$ with the standard contact structure. In particular, for any decomposable exact Lagrangian filling $L$ of a Legendrian link $K$, we may obtain a normal ruling of $K$ associated with $L$. We prove that the asso…

This paper gives two methods for constructing associative 3-folds in R^7, based around the fundamental idea of evolution equations, and uses these methods to construct examples of these geometric objects. The paper is a generalisation of the work by Joyce in math.DG/0008021, math.DG/0008155, math.DG/0010036 and math.DG…

Interestingness measures provide information that can be used to prune or select association rules. A given value of an interestingness measure is often interpreted relative to the overall range of the values that the interestingness measure can take. However, properties of individual association rules restrict the val…

This paper proposes a framework to learn explainable rules from knowledge graphs for better recommendation.

A prediscretisation of numerical attributes which is required by some rule learning algorithms is a source of inefficiencies. This paper describes new rule tuning steps that aim to recover lost information in the discretisation and new pruning techniques that may further reduce the size of rule models and improve their…

Deep learning optimizes user association in Massive MIMO networks.

SAERMA combines deep learning and rule mining to identify SNP interactions.

New examples of extremal Kähler metrics on blow-ups of parabolic ruled surfaces are constructed. The method is based on the gluing construction of Arezzo, Pacard and Singer. This enables to endow ruled surfaces of the form $\mathbb{P}(\mathcal{O}\oplus L)$ with special parabolic structures such that the associated iter…

Cannon, Swenson, and others have proved numerous theorems about subdivision rules associated to hyperbolic groups with a 2-sphere at infinity. However, few explicit examples are known. We construct an explicit subdivision rule for many 3-manifolds from polyhedral gluings. The manifolds that satisfy the conditions inclu…

Study of associative submanifolds in Berger space SO(5)/SO(3).

Study discovers rules linking patient symptoms to unplanned ICU transfers.

This study uses ARM to analyze pedestrian crashes under different lighting conditions.

This survey article discusses three aspects of knot colorings. Fox colorings are assignments of labels to arcs, Dehn colorings are assignments of labels to regions, and Alexander-Briggs colorings assign labels to vertices. The labels are found among the integers modulo n. The choice of n depends upon the knot. Each typ…

Predict and explain service failures in supply-chain networks using data models.

Associated to Legendrian links in the standard contact three-space, Ruling polynomials are Legendrian isotopy invariants, which also compute augmentation numbers, that is, the points-counting of augmentation varieties for Legendrian links (up to a normalized factor) \cite{HR15}. In this article, we generalize this pict…

New algebraic structure for vector bundles with special properties.

Advocates rule-based approach for multi-label classification.

The Berglund-Hübsch rule connects Calabi-Yau orbifolds to Sasakian manifolds.

Proposes SCR-Apriori for efficient mining of SCR-patterns.

Optimal classification rules control error rates in multiclass mixture models.

Poisson algebra is usually defined to be a commutative algebra together with a Lie bracket, and these operations are required to satisfy the Leibniz rule. We describe Poisson structures in terms of a single bilinear operation. This enables us to explore Poisson algebras in the realm of non-associative algebras. We stud…

The study constructs associative 3-folds in squashed 3-Sasakian manifolds.

Enhances Bayesian learning with rule-based evolutionary techniques.

Study of timelike surfaces with time-minimizing rulings in Newtonian and relativistic spacetimes.

We describe various sets of conditional independence relationships, sufficient for qualitatively comparing non-vanishing squared partial correlations of a Gaussian random vector. These sufficient conditions are satisfied by several graphical Markov models. Rules for comparing degree of association among the vertices of…

Classifies rank-one submanifolds in Euclidean space.

Learning to remember long sequences remains a challenging task for recurrent neural networks. Register memory and attention mechanisms were both proposed to resolve the issue with either high computational cost to retain memory differentiability, or by discounting the RNN representation learning towards encoding shorte…

Unified quadrature framework for large-scale kernel machines.

SigD2 reduces noisy rules in rule-based classifiers for better accuracy and readability.

Study on pricing rules for income streams with partial insider information.

Geodesics in R^n configuration spaces for points apart by epsilon.

Hybrid framework merges data and domain knowledge for better spatial interpolation.

The principal theory of this paper comprises a technique for constructing associative, coassociative and Cayley submanifolds of Euclidean space with symmetries, using first-order ordinary differential equations. Explicit examples of U(1)-invariant associative cones in R^7 and SU(2)-invariant Cayley 4-folds in R^8 are t…

The paper studies scaling laws for associative memory mechanisms.

CICLAD efficiently mines frequent closed itemsets from data streams with minimal memory usage.

In this note we apply a 4-fold sum operation to develop an associativity rule for the pairwise symplectic sum. This allows us to show that certain diffeomorphic symplectic $4$-manifolds made out of elliptic surfaces are in fact symplectically deformation equivalent. We also show that blow-up points can be traded from o…

DTOR explains anomalies with rule-based explanations.

Proof of wall-crossing formula using spectral networks.

In this paper we introduce the area of 2-ruled 4-folds in R^n (n=7 or 8), that is, submanifolds M of R^n that admit a fibration over some 2-fold Sigma such that each fibre is an affine 2-plane in R^n. This is motivated by the paper math.DG/0012060 by Joyce on ruled special Lagrangian 3-folds in C^3 and the work of the …

In a physical neural system, where storage and processing are intimately intertwined, the rules for adjusting the synaptic weights can only depend on variables that are available locally, such as the activity of the pre- and post-synaptic neurons, resulting in local learning rules. A systematic framework for studying t…

We study strictly proper scoring rules in the Reproducing Kernel Hilbert Space. We propose a general Kernel Scoring rule and associated Kernel Divergence. We consider conditions under which the Kernel Score is strictly proper. We then demonstrate that the Kernel Score includes the Maximum Mean Discrepancy as a special …