Bipartite networks are a common type of network data in which there are two types of vertices, and only vertices of different types can be connected. While bipartite networks exhibit community structure like their unipartite counterparts, existing approaches to bipartite community detection have drawbacks, including im…
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48 results for “bipartite data”
New model detects communities in bipartite networks with covariates.
problem Detecting communities in bipartite networks with covariates.
method Variational inference for fitting the model.
result Effectiveness of the model on simulated and real data.
New model for detecting communities in weighted bipartite networks.
problem Lack of models for weighted bipartite networks.
method Introducing Bipartite Distribution-Free model and its extension.
result Spectral algorithms for consistent estimation of node labels.
Cascade-BGNN efficiently learns node representations for large-scale bipartite graphs.
problem Efficiently learning node representations for large-scale bipartite graphs with limited labels.
method Cascade-BGNN uses customized Inter-domain Message Passing (IDMP) and Intra-domain Alignment (IDA) for efficient information aggregation.
result Cascade-BGNN achieves domain-consistent, self-supervised, and efficient node representation learning.
A new SBM for bipartite networks improves community detection in noisy data.
problem Community detection in bipartite networks with stochastic blockmodels.
method Bayesian nonparametric formulation of SBM for bipartite networks, algorithm to find communities efficiently.
result Improves community detection results over general SBMs, especially in noisy data.
A new method assesses similarity in bipartite data using reflexive regular equivalence.
problem Challenges in clustering bipartite data, especially in validating co-similarity assumptions.
method Uses spectral properties of a bipartite adjacency matrix and reflexive regular equivalence to estimate similarity.
result The method outperforms other measures in correctly classifying genes in real-world data.
New method for matching bipartite and unipartite graphs without collapsing.
problem Matching between bipartite and unipartite networks without losing information.
method Formulated as an undirected graphical model, aligns graphs without collapsing.
result Consistent method with conditions for exact recovery of matching solution.
Study explores properties of bipartite knots.
problem None explicitly stated; focuses on properties of bipartite knots.
method Exploration of combinatorial structure.
result Rich combinatorial structure of bipartite knots.
New method extends knot theory to non-bipartite knots, revealing PDs.
problem Extending knot theory to non-bipartite knots.
method Developed a new positive decomposition (PD) for HOMFLY polynomials of non-bipartite knots.
result PD exists for non-bipartite knots, not just bipartite ones.
Research tackles learning vertex representations for bipartite networks.
problem Lack of research on learning vertex representations for bipartite networks.
method Apply generic methods like node2vec and LINE, but ignore vertex type information.
result Generic methods are suboptimal for bipartite networks due to different properties and patterns.
Simplified Khovanov polynomials for bipartite links.
problem Computing Khovanov polynomials for bipartite links.
method Reduced Khovanov-Rozansky technique to Kauffman-Khovanov cycle calculus.
result Consistency demonstrated between reduced technique and bipartite Khovanov polynomials.
Improved model for grouping nodes in bipartite networks.
problem Challenges in grouping nodes in bipartite graphs.
method Introduced DC-LBM and developed variational EM algorithm.
result Significantly enhanced performance on real-world data.
Proposes new embeddings for bipartite graphs to better capture indirect relationships.
problem Typical graph embeddings fail to capture type-specific features in bipartite graphs.
method Develops two types of embeddings (FOBE and HOBE) that decompose edges into indirect relationships and uses algebraic distance for higher-order sampling.
result Ensemble embeddings improve performance over individual methods in link prediction and recommendation tasks.
Proposes a non-stationary LBM for dynamic bipartite networks.
problem Lack of time-varying intensity in latent block model for dynamic networks.
method Non-stationary temporal extension of LBM, greedy search for cluster and class membership.
result Maximizes exact integrated likelihood for clustering and class assignment.
Graph auto-encoder predicts user-item interactions from graph data.
problem Matrix completion for recommender systems from graph data.
method Differentiable message passing on bipartite graphs.
result Competitive performance on collaborative filtering benchmarks.
Bipartite graphs with more edges than a threshold have positive curvature.
problem Determining the curvature of bipartite graphs based on edge density.
method Using a new formula for Lin--Lu--Yau curvature, the study establishes conditions for bipartite graphs to have positive curvature.
result Bipartite graphs with more edges than the specified threshold have positive Lin--Lu--Yau curvature.
Extends interior polynomial to signed bipartite graphs and connects to HOMFLY polynomial.
problem Invariants of signed bipartite graphs and their relation to HOMFLY polynomial.
method Extending interior polynomial to signed bipartite graphs and showing equality to HOMFLY polynomial part.
result Interior polynomial of signed bipartite graphs equals part of HOMFLY polynomial for planar case.
New research finds six bipartite intrinsically knotted graphs with 23 edges.
problem Identifying intrinsically knotted bipartite graphs with 23 edges.
method Analyzing embeddings and graph minors to find minimal intrinsically knotted graphs.
result No minor minimal intrinsically knotted bipartite graph exists with 23 edges.
New invariant defined for complete and bipartite graphs, determining Thurston-Bennequin numbers.
problem Determining Thurston-Bennequin numbers for complete and bipartite Legendrian graphs.
method Defined a total Thurston-Bennequin number, showed its determination by 3-cycles for complete graphs and 4-cycles for bipartite graphs.
result The total Thurston-Bennequin number is a new invariant that determines Thurston-Bennequin numbers for complete and bipartite graphs.
Simplified Khovanov-Rozansky calculus for bipartite knots.
problem Complexity in calculating superpolynomials for knots.
method Bipartite calculus generalizes Khovanov-Rozansky calculus for a restricted class of knots.
result Simplification of Khovanov-Rozansky polynomials for bipartite knots.
Proves Khovanov homology has no torsion for bipartite circle graphs.
problem Proving properties of Khovanov homology for bipartite circle graphs.
method Proved homotopy equivalence of independence complexes to wedges of spheres.
result Extreme Khovanov homology has no torsion.
Improved bipartite link prediction using 2-hop paths.
problem Link prediction in bipartite networks without node attributes.
method Multiply reconstructed adjacency matrix with symmetrically normalized training adjacency matrix to form 2-hop paths.
result 2-hop paths improve link prediction performance.
Formula for interior polynomial of bipartite graphs derived from knot theory.
problem Deriving a formula for the interior polynomial of bipartite graphs.
method Applied knot theory, Ehrhart reciprocity, flyping and mutation.
result Proved a mirroring formula for the interior polynomial of bipartite graphs.
New model for detecting communities in weighted bipartite networks.
problem No model for community detection in overlapping bipartite weighted networks.
method Introduces BiMMDF model allowing any distribution with block structure.
result Efficient algorithm with theoretical guarantee of consistent estimation.
It is the main goal of this article to address the bipartite ranking issue from the perspective of functional data analysis (FDA). Given a training set of independent realizations of a (possibly sampled) second-order random function with a (locally) smooth autocorrelation structure and to which a binary label is random…
Model for operational risk using bipartite graphs and heavy-tailed distributions.
problem Capturing event type and business line structure in operational risk data.
method Statistical model based on heavy-tailed distributions and bipartite graphs.
result Reliable estimates of tail risk and capital allocations with small data sets.
A new method calculates HOMFLY-PT polynomials for bipartite links.
problem Computing HOMFLY-PT polynomials for bipartite links efficiently.
method Generalizes Goeritz matrix method for bipartite links.
result Reduces HOMFLY-PT polynomial calculation to matrix algebra.
We define integral odd Khovanov homology of principally unimodular bipartite graph-links.
PAC learning simplified as bipartite matching.
problem Efficiently solving PAC learning problems.
method Transductive learning and one-inclusion graphs.
result PAC learning can be reduced to bipartite matching.
We present a simple combinatorial model for quasipositive surfaces and positive braids, based on embedded bipartite graphs. As a first application, we extend the well-known duality on standard diagrams of torus links to twisted torus links. We then introduce a combinatorial notion of adjacency for bipartite graph links…
We present evidence in support of a conjecture that a bipartite graph with at least five vertices in each part and |E(G)| \geq 4 |V(G)| - 17 is intrinsically knotted. We prove the conjecture for graphs that have exactly five or exactly six vertices in one part. We also show that there is a constant C_n such that a bipa…
Develops a new variational estimator for node popularity in bipartite networks.
problem Estimating node popularity in bipartite networks with varying patterns.
method Variational Expectation-Maximization (VEM) framework for the Two-Way Node Popularity Model (TNPM).
result The proposed method achieves superior estimation accuracy across different types of networks.
The interior polynomial of a bipartite graph's hypergraph equals its Ehrhart polynomial of its root polytope.
problem Understanding the relationship between the interior polynomial of a bipartite graph and its root polytope.
method Proving equivalence between the interior polynomial of a bipartite graph's hypergraph and the Ehrhart polynomial of its root polytope.
result The interior polynomials of a bipartite graph and its transpose agree.
Improved text summarization using belief propagation on weighted bipartite graphs.
problem Text summarization from a graph theory perspective.
method Generalized belief propagation algorithm for weighted bipartite graphs.
result Our algorithm outperforms greedy methods in text summarization tasks.
Researchers compute connectivity of braid group in bipartite graph configuration space.
problem Understanding connectivity of braid group in complex configuration space.
method Analysis of topology, hidden symmetry, and literature results.
result Explicit computation of connectivity at infinity for braid group.
Discrete flows extend normalizing flows to discrete data, improving various applications.
problem Applying normalizing flows to discrete data distributions.
method Developed discrete autoregressive and bipartite flows, showing their effectiveness on various discrete data tasks.
result Discrete autoregressive flows outperform autoregressive baselines on synthetic discrete distributions and Potts models.
Incorrect parity-based descriptions of realizable Gauss diagrams found, but bipartite graphs provide a valid approach.
problem Incorrect descriptions of realizable Gauss diagrams using parity conditions.
method Used bipartite graphs to describe realizable Gauss diagrams.
result Realizable Gauss diagrams can be accurately described using bipartite graphs.
New method for calculating HOMFLY polynomials in symmetric representations.
problem Calculating HOMFLY polynomials for symmetric representations.
method Planar decomposition and projection to symmetric representations.
result Restoration of planarity and new insights into HOMFLY polynomials.
Study analyzes Colombian firms' export capabilities over 5 years.
problem Understanding specialization in Colombian firms' export products.
method Bipartite network analysis, modularity maximization, Louvain algorithm.
result Firms specialize in exporting specific product categories, forming clusters.
Bipartite Riemann-Finsler geometries with complementary Finsler structures are constructed. Calculable examples are presented based on a bilinear-form coefficient for explicit Lorentz violation.
Paper tackles high-dimensional bipartite ranking using PAC-Bayesian approach.
problem High-dimensional bipartite ranking problem.
method PAC-Bayesian approach with non-asymptotic risk bounds and oracle inequalities.
result Proves minimax optimality of the proposed scoring and ranking strategy.
Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systemsstat.ML
A new model detects common patterns in pollination networks.
problem Comparing organization of bipartite networks to understand community structure.
method colBiSBM, a family of probabilistic models for collections of bipartite networks.
result The method uncovers shared ecological roles and partitions networks.
We characterize which automorphisms of an arbitrary complete bipartite graph can be induced by a homeomorphism of some embedding of the graph in .
A graph is intrinsically knotted if every embedding contains a knotted cycle. It is known that intrinsically knotted graphs have at least 21 edges and that the KS graphs, and the 13 graphs obtained from by moves, are the only minor minimal intrinsically knotted graphs with 21 edges. This set incl…
Neural execution solves complex graph problems like bipartite matching.
problem Solving complex graph algorithms like maximum bipartite matching.
method Reduces bipartite matching to a flow problem and uses Ford-Fulkerson for maximum flow.
result Neural network achieves optimal matching almost 100% of the time.
Method disentangles network structures in financial systems.
problem Inferring network architecture from data.
method Belief Propagation for SBM and dcSBM, entropy maximization.
result Interbank network better described as bipartite, core-periphery structure emerges with aggregated data.
New tests detect communities in dense bipartite graphs with high accuracy.
problem Detecting communities in dense bipartite graphs with high accuracy.
method Non-asymptotic upper and lower bounds, novel minimax-optimal tests, hard-thresholded nonlinear statistics.
result Non-asymptotic upper and lower bounds match for any configuration of graph sizes.
Method proves complex homeomorphic to a sphere using bisimplices.
problem Proving regular CW complexes homeomorphic to spheres.
method Discrete Morse theory and bisimplices.
result Flag bisimplicial completion of quadric complexes is contractible.