Introduces 'social bow tie' to quantify tie strength in social networks.
problem Understanding tie strength and its influencing factors in social networks.
method Introduced 'social bow tie' framework, defined metrics, used random forests and regression models.
result Bow tie metrics are highly predictive of tie strength, and tie strength is influenced by overlapping and non-overlapping social circles.
Researchers create coordinates for hyperbolic surfaces, proving a magic formula.
problem Constructing coordinates for hyperbolic structures on genus-2 surfaces.
method Developed Fenchel-Nielsen coordinates and Wolpert's magic formula analogues.
result Found Darboux charts for the Goldman symplectic form on branched hyperbolic structures.
Systemic risks of default contagion in the Russian interbank market are investigated. The analysis is based on considering the bow-tie structure of the weighted oriented graph describing the structure of the interbank loans. A probabilistic model of interbank contagion explicitly taking into account the empirical bow-t…
Modelling of contagion in interbank networks is discussed. A model taking into account bow-tie structure and dissasortativity of interbank networks is developed. The model is shown to provide a good quantitative description of the Russian interbank market. Detailed arguments favoring the non-percolative nature of conta…
Classifies instantons on ALF multi-Taub-NUT spaces and ties them to bow solutions.
problem Classifying instantons on specific spaces.
method Uses Nahm's equations and bow solutions to construct instantons.
result Constructs holomorphic instanton bundles on multi-Taub-NUT spaces.
The study examines complex tangles in Curve Shortening Flow singularities.
problem Classifying all knots in R3 is a challenging problem. method Examine solutions to plane Curve Shortening Flow to identify tangles.
result A vanishing n-loop converges to a 'squeezed bow-tie' under rescaling. Study reveals structure of Bitcoin's crypto flow network.
problem Understanding crypto flows among Bitcoin users.
method Blockchain data, user identification, network construction, bow-tie structure, Hodge decomposition, non-negative matrix factorization.
result Users are located in upstream, downstream, and core of the crypto flow network.
Study of Bitcoin User Network structure over 8 years.
problem Analyzing Bitcoin User Network structure over time.
method Mesoscale structural properties analysis of Bitcoin User Network (BUN) from 2009 to 2017.
result Bitcoin User Network exhibits core-periphery structure with bow-tie topology, influenced by price fluctuations.
The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international …
Study XRP network, propose Flow Index to analyze transaction frequencies.
problem Analyze transaction frequencies in XRP network.
method Analyze XRP transaction history, propose Flow Index.
result Flow Index reveals bow-tie/walnut structure in XRP network.
Instantons on ALF spaces constructed from bow data.
problem Constructing instantons on Asymptotically Locally Flat spaces.
method Using bow data to represent ALF spaces and their moduli spaces, constructing anti-self-dual connections.
result Anti-self-dual connections on ALF spaces are instantons with finite action.
Monads link instantons and bow solutions in complex geometry.
problem Linking instantons and bow solutions via monads.
method Generalized ADHM-Nahm transform and monads.
result Established one-to-one correspondence between instantons and bow solutions.
Instantons on multi-Taub-NUT spaces are mapped to bow representations.
problem Mapping instantons to bow representations for multi-Taub-NUT spaces.
method Proving gauge equivalence classes correspondence and isometry of moduli spaces.
result Instantons on multi-Taub-NUT spaces are isometric to bow representations.
Classifies 85 tie knots into mathematical categories.
problem Classifying and understanding the mathematical properties of tie knots.
method Formal language and sequence of moves to describe tie knots, classification based on knot theory.
result Proves that any tie knot is prime and alternating.
Bayesian neural networks improve deep learning's accuracy and uncertainty estimation.
problem Overconfident predictions, adversarial attacks, and variability underestimation in deep models.
method Stochastic relaxation of feed-forward rectified neural networks with sparsity-promoting priors and Polya-Gamma data augmentation.
result Improved scalability and robustness to architectural design through approximate variational inference.
Singular monopoles are nonabelian monopoles with prescribed Dirac-type singularities. All of them are delivered by the Nahm's construction. In practice, however, the effectiveness of the latter is limited to the cases of one or two singularities. We present an alternative construction of singular monopoles formulated i…
Yang-Mills instantons on ALE gravitational instantons were constructed by Kronheimer and Nakajima in terms of matrices satisfying algebraic equations. These were conveniently organized into a quiver. We construct generic Yang-Mills instantons on ALF gravitational instantons. Our data are formulated in terms of matrix-v…
Efficient algorithms decide algebraic constraints of causal graphs.
problem Distinguish causal graphs with latent confounders.
method Study algebraic constraints and propose efficient algorithms.
result Decide equivalence or subset of algebraic constraints.
Identifying causal direction in location-scale noise models with hidden variables
problem Causal discovery in location-scale noise models with hidden variables
method ADMGs satisfying a bow-free condition
result First identifiability result for causally insufficient models beyond noise additivity
Simple BoW model outperforms complex embeddings in knowledge graphs.
problem Improving knowledge graph embeddings for efficient training and performance.
method Used a Bag-of-Words (BoW) approach to model co-occurrences of entities and relations.
result Simple BoW model achieves state-of-the-art performance in knowledge graph tasks.
TIE framework detects out-of-distribution samples and estimates uncertainty without external datasets.
problem Detecting and estimating uncertainty for out-of-distribution samples in neural networks.
method TIE framework extends a classifier to an (n+1)-class model, iteratively refining through training, inversion, and exclusion.
result Unified and interpretable framework for robust anomaly detection and calibrated uncertainty estimation.
We consider the problem of structure learning for bow-free acyclic path diagrams (BAPs). BAPs can be viewed as a generalization of linear Gaussian DAG models that allow for certain hidden variables. We present a first method for this problem using a greedy score-based search algorithm. We also prove some necessary and …
Hashing, or learning binary embeddings of data, is frequently used in nearest neighbor retrieval. In this paper, we develop learning to rank formulations for hashing, aimed at directly optimizing ranking-based evaluation metrics such as Average Precision (AP) and Normalized Discounted Cumulative Gain (NDCG). We first o…
Improved emotion prediction using autoencoder codebooks.
problem Continuous emotion prediction from audio data.
method Bag-of-Words model based on autoencoder codebook.
result Improved CCC scores for emotion dimensions.
New satellite constructions create infinite Brunnian links.
problem Creating new Brunnian links from existing ones.
method Satellite sum and satellite tie constructions.
result Every Brunnian link has a unique tree-arrow structure.
Study financial contagion and risk in sparse networks with directed edges.
problem Analyzing systemic risk in sparse financial networks with balance-sheet interactions.
method Linear fraction of institutions with zero out-degree, sender-truncated subgraph G_sh, adversarial and random systemic events, explicit fan-in accumulation bound.
result Maximal forward reachability in G_sh is O(log n) with high probability in the subcritical regime, and multi-hit defaults are negligible in the supercritical regime.
This research applies fuzzy clustering to reduce high-dimensional text data.
problem High-dimensional sparse vectors in bag-of-words matrices.
method Fuzzy clustering as a DR method based on Unsupervised Feature Transformation (UFT).
result Fuzzy clustering outperforms PCA and SVD in reducing high-dimensional text data.
This paper gives mathematical models for flat knotted ribbons, and makes specific conjectures for the least length of ribbon (for a given width) needed to tie the trefoil knot and the figure eight knot. The first conjecture states that (for width one) the least length of ribbon needed to tie an open-ended trefoil knot …
Study instanton metrics via Taub-NUT deformations.
problem Understanding deformations of instanton metrics.
method Using generalized Legendre transform on bow varieties.
result Found Kähler potential on instanton moduli spaces.
Characterizes Lebesgue points using nearest neighbor methods.
problem Consistency of classification algorithms based on nearest neighbors.
method Characterization of Lebesgue points via 1-Nearest Neighbor regression.
result Proves convergence of 1-Nearest Neighbor classification algorithms in metric spaces.
We solve structure learning for cyclic linear causal models using observational data.
problem Learning the structure of cyclic linear causal models from observational data.
method Assuming simple graphs, we use a criterion for distributional equivalence and implement a greedy search method.
result We show that simple cyclic models are of expected dimension and justify score-based methods for structure learning.
We study finite action anti-self-dual Yang-Mills connections on the multi-Taub-NUT space. We establish the curvature and the harmonic spinors decay rates and compute the index of the associated Dirac operator. This is the first in a series of papers proving the completeness of the bow construction of instantons on mult…
New method uses word subspaces and term-frequency to improve text classification.
problem Lack of semantic meaning in bag-of-words features.
method Proposes word subspaces and term-frequency weighted word subspaces for text classification.
result Improved text classification performance compared to state-of-the-art algorithms.
We present ADHM-Nahm data for instantons on the Taub-NUT space and encode these data in terms of Bow Diagrams. We study the moduli spaces of the instantons and present these spaces as finite hyperkahler quotients. As an example, we find an explicit expression for the metric on the moduli space of one SU(2) instanton. W…
In this paper the problem of optimal derivative design, profit maximization and risk minimization under adverse selection when multiple agencies compete for the business of a continuum of heterogenous agents is studied. The presence of ties in the agents' best-response correspondences yields discontinuous payoff functi…
Differential Evolution outperforms SMAC in hyperparameter tuning.
problem Automated hyperparameter tuning for machine learning.
method Empirical study comparing Differential Evolution to SMAC.
result Differential Evolution outperforms SMAC on most datasets.
Researchers create a partial resolution of Coulomb branches for gauge theories.
problem Understanding partial resolutions of Coulomb branches in gauge theories.
method Constructing partial resolutions as variants of generalized slices in geometric contexts.
result Identified partial resolutions with specific geometric objects.
Statistical framework improves LLM chatbot ranking.
problem Improving evaluation of LLM-based chatbots through pairwise comparisons.
method Factored tie model, covariance modeling, and parameter constraints.
result Substantial improvements in modeling pairwise comparison data.
Characterizes submanifolds with minimum ratio of diameter to focal radius.
problem Finding submanifolds with the minimum ratio of extrinsic diameter to focal radius.
method Combining K. Sakamoto's classification of submanifolds with planar geodesics and A. Schur's Bow Lemma for space curves.
result Essentially round spheres or Veronese embeddings of projective spaces achieve the minimum ratio.
Quantifies Schur's theorem for curves in CAT(k) spaces.
problem Quantifying Schur's comparison theorem for curves in CAT(k) spaces.
method Comparison formula for curves in model planes, curvature measures, moment arm, and Reshetnyak's theorem.
result Sharpens and extends classical arm and bow lemmas and Riemannian analogues.
We improve robust parameter estimation in causal models from observational data.
problem Robustly estimating parameters in linear structural equation models from observational data.
method Extending Sankararaman et al. (2019) to a broader class of models, providing sufficient conditions for robust identifiability.
result For a large set of parameters, robust identifiability holds and existing algorithms achieve robust identifiability.
Paper explains dynamics of homeomorphisms to mapping tori geometry.
problem Understanding dynamics of end-periodic homeomorphisms.
method Illustration-driven overview of recent results.
result Analogue of Brock's theorem for infinite-type surfaces.
What length of rope (of given diameter) is required to tie a particular knot? To answer this question, we define some new notions of thickness for a space curve, one based on Gromov's distortion, and another generalizing the thickness of Litherland, Simon et al. We prove a basic inequality between these thickness measu…
C-index varies among software, complicating model comparison.
problem Variation in C-index calculations across software.
method Comparison of C-index estimators in R and Python.
result Different implementations yield varying results.
Alternating-sign Hopf plumbing along a tree yields fibered alternating links whose homological monodromy is, up to a sign, conjugate to some alternating-sign Coxeter transformation. Exploiting this tie, we obtain results about the location of zeros of the Alexander polynomial of the fibered link complement implying a s…
HAXMLNet tackles extreme multi-label text classification with hierarchical attention.
problem Tagging each text with relevant labels from an extreme-scale label set.
method Proposes a hierarchical structure with multi-label attention for efficient and effective XMTC.
result HAXMLNet achieves competitive performance compared to state-of-the-art methods.
New language models improve essay scoring accuracy.
problem Improving essay scoring accuracy using AI.
method Used BERT and XLNet language models to compare with traditional methods.
result Achieved above human-level accuracy on AES dataset.
New method learns graph structure with hidden causes from observational data.
problem Learning the structure of linear non-Gaussian models with hidden causes.
method Augments hidden variable structure by learning multidirected edges and uses higher order cumulants.
result Correct structure recovery for bow-free acyclic mixed graphs with multi-directed edges.