FAA identifies rodent disease carriers for human health.
problem Identifying rodent species that carry zoonotic diseases.
method Applied Formal Concept Analysis to rodent trait data.
result Identified concepts linking rodent traits to zoonotic disease carrier status.
FCA2VEC embeds formal concept analysis data for large datasets.
problem Embedding formal concept analysis data for large datasets.
method Introducing fca2vec, a family of embedding techniques for formal concept analysis.
result Retrieves cover relation of a concept lattice from a computational feasible embedding.
Extends linear representation hypothesis to categorical and hierarchical concepts in LLMs.
problem Representing concepts without natural contrasts in large language models.
method Formalizes linear representation hypothesis for categorical and hierarchical concepts, proving relationships between concept hierarchy and representation geometry.
result Validated theoretical results on large language models, estimating representations for 900+ concepts.
Method learns graph from data clusters using FCA.
problem Learning graph representation from multivariate data.
method Uses formal concept analysis (FCA) to extract hierarchical relationships between clusters.
result Empirically shows superior hierarchical structure extraction compared to baseline.
This tutorial explains FCA and its applications in data analysis.
problem Data representation and analysis challenges.
method Formal Concept Analysis (FCA) as a mathematical tool for knowledge representation and data analysis.
result FCA is a powerful tool for knowledge representation and data analysis.
In this paper, we study the formal solution space of a nonlinear PDE in a fiber bundle. To this end, we start with foundational material and introduce the notion of a pfd structure to build up a new concept of profinite dimensional manifolds. We show that the infinite jet space of the fiber bundle is a profinite dimens…
New biclustering algorithms for microarray data using Formal Concept Analysis.
problem Uncovering patterns in gene expression data matrices.
method Formal Concept Analysis and Association Rules.
result Promising results from proposed biclustering algorithms.
Formalizes concepts as latent variables in hierarchical models for high-dimensional data.
problem Lack of formalization and theoretical insights for learning discrete concepts from high-dimensional data.
method Formalizes concepts as latent causal variables in a hierarchical model, formulates conditions for concept identification.
result Conditions for identifying latent hierarchical models in unsupervised data, handling complex structures and high-dimensional data.
The paper formalizes how concepts are encoded in text-guided generative models and provides a method to manipulate them.
problem Encoding and manipulating concepts in text-guided generative models.
method Formalizing concepts as subspaces of a representation space, developing algebraic manipulation methods.
result The ability to manipulate concepts in generative models through algebraic operations on the representation.
We formalize financial concepts and prove Cox-Ross-Rubinstein model completeness.
problem Proving completeness of financial models.
method Formalization in Isabelle/HOL, proving completeness under no-arbitrage condition.
result Every derivative product in Cox-Ross-Rubinstein model has a unique fair price.
The paper advances OA-biclustering for multi-mode community detection in social networks.
problem Mining meaningful patterns in multi-mode networks for community detection.
method Object-attribute biclustering (OA-biclustering) for 2-mode networks, extended to 3- and 4-mode networks.
result OA-biclusters are suitable for community detection in multi-mode cases, even with unknown number of corresponding n-cliques. Paper formalizes Simon's satisficing through FFSD, proving its equivalence to expected utility theory.
problem Formalizing Herbert Simon's bounded rationality concept in economic decision-making.
method Developed FFSD framework using Lean 4 theorem prover, proving equivalence to expected utility theory.
result Equivalence theorem linking FFSD to expected utility maximization for approximate indicator functions.
New equivariant formality concepts solve the toral rank conjecture.
problem Toral rank conjecture and equivariant formality of actions.
method Rational homotopy theory, Hirsch-Brown models, A-infinity algebras.
result Actions with new properties satisfy the toral rank conjecture.
Defines formal vertex laws related to Lie conformal algebras.
problem No specific problem stated; focuses on definitions and proofs.
method Definitions and proofs of vertex/conformal versions of classical Lie theory results.
result Proves vertex/conformal versions of important Lie theory results.
Paper introduces new graph concepts for better modeling of temporal interactions.
problem Graph theory struggles to capture temporal and structural aspects of interactions.
method Generalizes graph concepts to handle both temporal and structural aspects of interactions.
result Formalism allows direct modeling of interactions over time, similar to graph theory.
The Lagrangian formalism on a arbitrary non-fibrating manifold is considered. The kinematical description of this generic situation is based on the concept of (higher-order) Grassmann manifolds which is the factorization of the regular velocity manifold to the action of the differential group. Here we introduce in this…
Owners of a web-site are often interested in analysis of groups of users of their site. Information on these groups can help optimizing the structure and contents of the site. In this paper we use an approach based on formal concepts for constructing taxonomies of user groups. For decreasing the huge amount of concepts…
Interpretable ML methods for better decision-making with explanations.
problem Lack of transparency in black-box ML models.
method Use of Formal Concept Analysis and cooperative game theory to assess attribute importance and reduce attribute count.
result Developed methods to assess attribute importance and reduce attribute count in ML models.
Formally proves machine learning for simple classifiers.
problem Proving PAC learnability for decision stumps.
method Formal proof in Lean, separating deterministic and probabilistic proofs.
result Formal proof of PAC learnability for decision stumps.
This work explains how linear representations in large language models arise from training objectives and gradient descent.
problem Understanding the origins of linear representations in large language models.
method A latent variable model to abstract and formalize concept dynamics, combined with analysis of the softmax cross-entropy objective and gradient descent.
result Linear representations emerge when learning from data matching the latent variable model, and this simple structure suffices to yield linear representations.
A new algorithm uses FCA to recommend the best classifier for each object.
problem Improving classification accuracy by selecting the right classifier for each object.
method Formal Concept Analysis (FCA) is used to recommend the best classifier for each object based on the assumption that a classifier is likely to predict the label correctly if its neighbors have done so.
result The method significantly improves classification accuracy compared to using a single classifier.
Using the concept of s-formality we are able to extend the bounds of a Theorem of Miller and show that a compact k-connected 4k+3- or 4k+4-manifold with b_{k+1}=1 is formal. We study k connected n-manifolds, n= 4k+3, 4k+4, with a hard Lefschetz-like property and prove that in this case if b_{k+1}=2, then the manifold i…
This paper formalizes manifolds in positive characteristic varieties.
problem Establishing l-adic formal manifold structures on positive characteristic varieties.
method Develops and proves the existence of l-adic formal manifold structures and abelianized Galois symmetries.
result Proves l-adic homotopic equivalence and l-local lifting for simply-connected varieties.
Quaternionic differential geometry expands geometric concepts using quaternions.
problem Generalizing geometric concepts to quaternionic constraints.
method Generalizing curves and surfaces, curvature, torsion, differential forms, and directional derivatives to quaternionic constraints.
result Quaternionic formalism provides a suitable language for differential geometry.
Neurosymbolic predictors fail to model uncertainty under independence assumption.
problem Neurosymbolic predictors' reliance on independence assumption limits their ability to model uncertainty.
method Formal analysis of NeSy predictors under independence assumption.
result Assuming independence among symbolic concepts prevents NeSy predictors from representing uncertainty.
We prove a Darboux theorem for formal deformations of Hamiltonian operators of hydrodynamic type (Dubrovin-Novikov). Not all deformations are equivalent to the original operator: there is a moduli 2-stack of normal forms. The paper utilizes three main concepts: 1) dg Lie algebras concentrated in degrees [-1,\infty) suc…
A new BMF algorithm outperforms existing methods using MDL.
problem Developing a BMF algorithm that performs well across multiple metrics.
method From-below Boolean matrix factorization algorithm based on MDL principle.
result The proposed algorithm outperforms existing methods in various experiments.
Abstract: Formalizes metric spaces with coarse properties, generalizing finite decomposition complexity.
problem Understanding metric spaces with coarse properties.
method Formalizing and generalizing finite decomposition complexity.
result Determines sufficient conditions for metric spaces to satisfy Property A.
The paper introduces new concepts to understand natural phenomena through topology and dynamics.
problem Understanding natural phenomena like tornado formation using topology and dynamics.
method Developed new theoretical concepts and models for 2-dimensional and solid 2-dimensional 0-surgery.
result Enhanced understanding of natural phenomena through topology and dynamics.
Unified approach to learn interpretable concepts from data.
problem Building interpretable machine learning models and highly-performing foundation models.
method Relating causal representation learning and foundation models, defining concepts and proving their recoverability.
result Provable recovery of human-interpretable concepts from diverse data.
In this paper we introduce the concept of Hamiltonian system in the canonical and Poisson settings. We will discuss the quantization of the Hamiltonian systems in the Poisson context, using formal deformation quantization and quantum group theories.
Diffieties formalize geometrically the concept of differential equations. We introduce and study Hamilton-Jacobi diffieties. They are finite dimensional subdiffieties of a given diffiety and appear to play a special role in the field theoretic version of the geometric Hamilton-Jacobi theory.
We develop here a concept of deformed algebras through three examples and an application. Deformed algebras are obtained from a fixed algebra by deformation along a family of indexes, through formal series. We show how the example of deformed algebra used in \cite{Ma2013} is only an example among others, and how they o…
New methods identify concepts in trained embeddings reliably without human labels.
problem Identifying interpretable concepts in trained embedding spaces without human labels.
method Explicitly connecting concept discovery to PCA and ICA, proposing novel approaches for dependent concepts.
result Proven methods outperform competitors on a variety of experiments, achieving up to 29% better alignment with ground truth.
New algebraic formalism for differential calculus in Diolic algebras.
problem Studying differential calculus in vector bundles.
method Introducing functors of differential calculus over arbitrary graded commutative algebras (DCGCA) and applying this to Diolic algebras.
result Recovery of well-known objects and notions from ordinary differential, symplectic, and Poisson geometry, with unique aspects.
Formalizes learning algorithm invariances using category theory.
problem Understanding and characterizing invariances in learning algorithms.
method Using category theory to define and formalize invariances of learning algorithms.
result Illustrated and contrasted the invariances of linear regression and ridge regression.
New logic approach to machine learning prediction.
problem Predicting based on finite samples.
method Formalized measure of belief violations in modal Logic of Observations and Hypotheses (LOH).
result Machine learning algorithms minimize their version of incongruity.
VALC provides concept-level interpretations of FLMs, overcoming word-level limitations.
problem Lack of higher-level structure interpretation in FLMs' attention weights.
method Formal definition of conceptual interpretation, variational Bayesian framework (VALC).
result VALC finds optimal language concepts for FLM predictions, providing concept-level interpretations.
The jet formalism for Classical Field theories is extended to the setting of Lie algebroids. We define the analog of the concept of jet of a section of a bundle and we study some of the geometric structures of the jet manifold. When a Lagrangian function is given, we find the equations of motion in terms of a Cartan fo…
Paper introduces a method to explain concept drift using counterfactual explanations.
problem Understanding the features where concept drift occurs for better model adjustment.
method Formal definition and algorithm based on counterfactual explanations.
result Demonstrates usefulness of the method in various examples.
New formalization of curved spaces using pointwise affine spaces.
problem Traditional curved space formalizations like manifolds are complex.
method Introduces pointwise affine spaces and new geometric definitions.
result Simplified and clearer geometric concepts and results.
Newtonian, Lagrangian, and Hamiltonian dynamical systems are well formalized mathematically. They give rise to geometric structures describing motion of a point in smooth manifolds. Riemannian metric is a different geometric structure formalizing concepts of length and angle. The interplay of Riemannian metric and its …
Paper defines XAI concepts using category theory.
problem Lack of precise mathematical definitions for XAI.
method Uses Category theory to define XAI concepts rigorously.
result Establishes a theoretical foundation for XAI.
New approach to Lagrangian systems using intrinsic geometry.
problem Developing a new framework for Lagrangian systems.
method Direct reformulation of Hamiltonian formalism, introduction of spatial equation and spatial-gauge symmetry.
result Covariant and non-covariant canonical variational principles demonstrated for Maxwell equations.
Under appropriate assumptions, we generalize the concept of linear almost Poisson struc- tures, almost Lie algebroids, almost differentials in the framework of Banach anchored bundles and the relation between these objects. We then obtain an adapted formalism for mechanical systems which is illustrated by the evolution…
From positions, attained by modern theoretical physics in understanding of the universe bases, the methodological and philosophical analysis of fundamental physical concepts and their formal and informal connections with the real economic measurings is carried out. Procedures for heterogeneous economic time determinati…
Historically tensor calculus emerged in an attempt to formalize Rie- mann's ideas. We show that tensor calculus can be based also on Lie's idea of a transformation group and this approach leads quite naturally to the concept of deformation of a transformation group and the Kodaira- Spencer map.
Develops geometric quantum mechanics in infinite dimensions.
problem Quantum dynamics in infinite-dimensional spaces.
method Tulczyjew triple concept for Lagrangian formalism.
result Self-adjoint operators as Lagrangian submanifolds.