Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,341 papers · 148 categories

Trend · papers per month

17335066 · Jun 202019922001200920182026
48 results for combinatorial criteria

New criteria judge combinatorial equivalence of polytopes to products of simplices.

problem Determining combinatorial equivalence of polytopes to products of simplices.
method Combination of combinatorial, geometric, and topological conditions inspired by toric topology.
result New criteria for judging combinatorial equivalence of polytopes to products of simplices.

New framework for resilient bi-criteria optimization under noisy feedback.

problem Bi-criteria combinatorial optimization with noisy function evaluations.
method Introducing (α,β,δ,extttN)(α,β,δ, exttt{N})-resilience and developing a black-box framework.
result Achieves sublinear regret and constraint violation for bi-criteria bandit problems.

In this article we give combinatorial criteria to decide whether a transitive cyclic combinatorial d-manifold can be generalized to an infinite family of such complexes, together with an explicit construction in the case that such a family exists. In addition, we substantially extend the classification of combinatorial…

2011-12-05abs ↗pdf ↗

New criteria for relative hyperbolicity in hierarchically hyperbolic spaces.

problem Characterizing relative hyperbolicity in hierarchically hyperbolic spaces.
method New formulation of relative hyperbolicity in terms of hierarchy structures, applied to graphs associated to surfaces.
result The separating curve graph of a surface is relatively hyperbolic when the surface has zero or two punctures.

Online learning with one-sided feedback aims to maximize accuracy while ensuring fairness.

problem Maximizing accuracy in online learning with limited feedback and ensuring fairness.
method Extending the framework of Bechavod et al. (2020) to incorporate dynamic panels of auditors, reducing the problem to a contextual combinatorial semi-bandit, and leveraging Exp2 and Context-Semi-Bandit-FTPL algorithms.
result Multi-criteria no regret guarantees for accuracy and fairness are provided.

Paper studies geometric and combinatorial properties of circular snakes.

problem Exploring geometric and combinatorial properties of circular snakes.
method Definition and investigation of outer Lipschitz geometry, decomposition of Valette link, construction of combinatorial objects, weakly outer Lipschitz classification.
result Existence of canonical decomposition and necessary/sufficient criteria for removing segments or Hölder triangles.

We say that a cover of surfaces S -> X has the Birman--Hilden property if the subgroup of the mapping class group of X consisting of mapping classes that have representatives that lift to S embeds in the mapping class group of S modulo the group of deck transformations. We identify one necessary condition and one suffi…

2013-09-14abs ↗pdf ↗

The paper proves a new stability condition for certain Fano varieties.

problem Stability conditions for Fano varieties with Gorenstein singularities.
method Using toric test configurations and combinatorial criteria.
result Asymptotic Chow semistability implies Ding polystability for Gorenstein toric Fano varieties.

Optimal experiments tighten causal effect bounds efficiently.

problem Selecting experiments to tighten causal effect bounds from observational data.
method Formalized as max-potency problem, NP-hard. Polynomial-programming framework with graphical pruning criteria.
result Pruning criteria reduce search space significantly, enabling efficient experiment selection.

Algorithm selects optimal segment for physiological signal analysis.

problem Physiological signals are often corrupted by noise, requiring selective analysis.
method Combines deep neural networks for signal analysis and combinatorial optimization for segment selection.
result Significant improvement in system performance, e.g. 2.4% increase in sensitivity for heart sound segmentation.

Saddle connection complexes are rigid under affine equivalence.

problem Characterizing the rigidity of saddle connection complexes.
method Proving simplicial isomorphisms between saddle connection complexes are induced by affine diffeomorphisms.
result Saddle connection complexes are complete invariants of affine equivalence classes of half-translation surfaces.

Relational Structural Causal Models enable causal reasoning about unseen object combinations.

problem Developing a model that can reason about causal and combinatorial aspects of unseen object combinations.
method Relational Structural Causal Models extend structural causal models to include relational variables and define identification criteria.
result Proposed relational neural causal models outperform non-relational baselines on simulated traffic scenes.

This paper tackles JSSP with uncertain task durations using DRL.

problem Job Shop Scheduling Problem with uncertain task durations.
method Integrates Graph Neural Networks (GNNs) and Deep Reinforcement Learning (DRL) to generate robust schedules.
result Advances DRL applications to JSSPs, enhancing generalization and scalability.

We give some general criteria of being a homeomorphism for continuous mappings of topological manifolds, as well as criteria of being a diffeomorphism for smooth mappings of smooth manifolds. As an illustration, we apply these criteria to the problems arising in two- and three-dimensional grid generation.

2015-04-05abs ↗pdf ↗

The study reveals flaws in pruning criteria and proposes a new assumption for better filter selection.

problem Flaws in existing pruning criteria for CNNs.
method Empirical experiments and Convolutional Weight Distribution Assumption.
result The Convolutional Weight Distribution Assumption improves filter selection in pruning.

Improved recommendations using latent embeddings from user reviews.

problem Lack of consideration for latent embeddings in multi-criteria recommender systems.
method Utilized variational autoencoders to map user reviews into latent embeddings, which are then compressed into discrete vectors for multi-criteria recommendation.
result The proposed method significantly outperforms baselines across various datasets and evaluation measures.

New criteria for Heegaard splittings ensure strong irreducibility and finite Goeritz groups.

problem Determining strong irreducibility and finite Goeritz groups of Heegaard splittings.
method Two diagrammatic criteria for Heegaard splittings, accepting arbitrary disk systems.
result Criteria ensure strong irreducibility and finite Goeritz groups for Heegaard splittings.

Develops scenario theory for multi-criteria decision making.

problem Need for robustness assessment with multiple criteria and datasets.
method Collectively treats risks associated with individual criteria for multi-criteria decision problems.
result More accurate robustness certificates and sharper quantification of simultaneous criterion satisfaction.

We consider the problem of identifying patterns in a data set that exhibit anomalous behavior, often referred to as anomaly detection. In most anomaly detection algorithms, the dissimilarity between data samples is calculated by a single criterion, such as Euclidean distance. However, in many cases there may not exist …

2011-10-17abs ↗pdf ↗

The paper evaluates criteria for selecting cryptocurrencies based on historical data.

problem High risk of cryptocurrencies due to volatility.
method Characterized returns and risks using historical data in short time windows (7 and 15 days). Analyzed the importance of criteria using various methods.
result Importance of criteria for selecting cryptocurrencies is analyzed and evaluated.

New criteria detect anomaly detection algorithms without labeled data.

problem Lack of labeled data for evaluating anomaly detection algorithms.
method Developed two new criteria based on Excess-Mass and Mass-Volume curves, and a feature sub-sampling methodology.
result Empirically validated new criteria outperform classical ROC and PR curves in non-labeled data scenarios.

The paper analyzes performance criteria for competing fund managers in Ito-diffusion markets.

problem Analyzing performance of competing fund managers in Ito-diffusion markets.
method Developed forward relative performance criteria and forward Nash equilibrium for passive and competitive cases.
result Extended performance criteria for investment problems in Ito-diffusion markets.

A new Tsallis entropy criterion unifies decision tree split criteria.

problem Improving decision tree performance using a unified split criterion.
method Proposes a Tsallis Entropy Criterion (TEC) algorithm to unify Shannon entropy, Gain Ratio, and Gini index.
result TEC algorithm achieves statistically significant improvement over classical algorithms.

The paper introduces combinatorial Calabi flows to find hyperbolic metrics on surfaces with boundary.

problem Finding hyperbolic metrics on surfaces with totally geodesic boundaries of given lengths.
method Introducing combinatorial Calabi flows and proving their long time existence and global convergence.
result Proves the long time existence and global convergence of combinatorial Calabi flow on surfaces with boundary.

Turnpike results for risk tolerance in incomplete markets under time-monotone criteria.

problem Turnpike results for risk tolerance in incomplete markets under time-monotone criteria.
method Time-monotone forward performance criteria, analysis of limits, dependence on measure support.
result Temporal and spatial limits do not coincide and depend on measure support.

Sparse GEMINI selects relevant features for clustering without assumptions.

problem Feature selection in clustering with relevant clusters and variables.
method Discriminative clustering model maximizing GEMINI with l1 penalty.
result Sparse GEMINI selects relevant subsets of variables without prior hypotheses.

A new method for multi-criteria recommender systems using graph attention networks.

problem Lack of nuanced relationships between users and items based on specific criteria.
method MDGAT, a multi-edge bipartite graph with dual attention networks and contrastive learning.
result MDGAT achieves higher accuracy in predicting item ratings compared to baseline methods.

A game-theoretic approach to multi-criteria ranking from ordinal data.

problem Ranking objects from ordinal data with multiple criteria.
method Generalizing von Neumann winner to multi-criteria setting using Blackwell's approachability.
result The Blackwell winner can be computed as a convex optimization problem and achieves near-optimal sample complexity.

The paper develops algorithms for finding metrics with prescribed combinatorial curvature on polyhedral surfaces.

problem Finding metrics with prescribed combinatorial curvature on polyhedral surfaces.
method Discrete uniformization theorem, combinatorial α-Yamabe flow, combinatorial α-Calabi flow, edge flipping surgery.
result Longtime existence and convergence of combinatorial α-Yamabe flow and combinatorial α-Calabi flow with surgery.

Proposes a multi-criteria AutoML system to optimize additional criteria like fairness and interpretability.

problem Current AutoML systems limit model choices and preprocessing steps, ignoring secondary criteria.
method Optimizes additional criteria directly to guide the search for optimal machine learning pipelines.
result Demonstrates the need and usefulness of a multi-criteria AutoML system.

The paper introduces combinatorial curvature and flow for polyhedral surfaces, proving rigidity and solving the Yamabe problem.

problem Discrete conformal structures on polyhedral surfaces and their rigidity.
method Parameterized combinatorial curvature, combinatorial α-Ricci flow, and flow extension through singularities.
result Existence and convergence of combinatorial α-Ricci flow for solving the Yamabe problem.

Introduces new performance criteria for investment under distorted probabilities.

problem Reconciling time-consistent performance with probability distortions.
method Two definitions of forward rank-dependent criteria, equivalence established; characterization of viable probability distortion processes.
result Characterization of optimal wealth process and new distorted measure.

The paper introduces risk consistency properties for credit ratings.

problem Promoting prudent investment decisions in credit ratings.
method Introducing and studying risk consistency properties in the framework of Choquet rating criteria.
result Characterization of Choquet risk measures and rating criteria satisfying risk consistency properties.