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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.

168,982 papers · 148 categories

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12.5%25.0%37.5%50.0% · May 199319922001200920172026
48 results for combinatorial quantities

Goussarov, Polyak, and Viro proved that finite type invariants of knots are ``finitely multi-local'', meaning that on a knot diagram, sums of quantities, defined by local information, determine the value of the knot invariant. The result implies the existence of Gauss diagram combinatorial formulas for finite type inva…

2007-11-26abs ↗pdf ↗

A sign is introduced in the usual Laplacian on graphs and the corresponding analogue of the isoperimetric constant for this Laplacian is presented, i.e. a geometric quantity which enables to bound from above and below the first eigenvalue. The introduction of the sign in the Laplacian is motivated by the study of 22-l…

2014-10-22abs ↗pdf ↗

Following the work of Cano and Diaz, we consider a continuous analog of lattice path enumeration. This allows us to define a continuous version of any discrete object that counts certain types of lattice paths. We define continuous versions of binomials and multinomials, and describe some identities and partial differe…

2017-07-06abs ↗pdf ↗

We study the connections between link invariants, the chromatic polynomial, geometric representations of models of statistical mechanics, and their common underlying algebraic structure. We establish a relation between several algebras and their associated combinatorial and topological quantities. In particular, we def…

2008-06-20abs ↗pdf ↗

A matroid is a notion of independence in combinatorial optimization which is closely related to computational efficiency. In particular, it is well known that the maximum of a constrained modular function can be found greedily if and only if the constraints are associated with a matroid. In this paper, we bring togethe…

2014-03-20abs ↗pdf ↗

Let MM be a compact 3-manifold with a triangulation ττ. We give an inequality relating the Euler characteristic of a surface FF normally embedded in MM with the number of normal quadrilaterals in FF. This gives a relation between a topological invariant of the surface and a quantity derived from its combinatorial …

2008-10-01abs ↗pdf ↗

The paper introduces submodular information measures for machine learning applications.

problem Generalizing information-theoretic measures to non-random variables.
method Developing combinatorial information measures based on submodular functions.
result Submodular mutual information is submodular in one argument for certain submodular functions.

A new combinatorial approach groups regression coefficients for improved accuracy.

problem Grouping regression coefficients to reveal shared values within groups.
method Introduces L0L_0-Fusion, a combinatorial grouping approach using mixed integer optimization.
result L0L_0-Fusion achieves grouping consistency under weak grouping sensitivity conditions.

Translation surfaces with poles correspond to meromorphic differentials on compact Riemann surfaces. They appear in compactifications of strata of the moduli space of Abelian differentials and in the study of stability conditions. Such structures have different geometrical and dynamical properties than usual translatio…

2016-03-22abs ↗pdf ↗

New method improves solving combinatorial optimization problems with smoothed policies.

problem Solving combinatorial optimization problems repeatedly with varying instances.
method Smoothed policies with controlled random perturbations to linear oracle, leading to differentiable surrogate risk.
result Generalization bound decomposes excess risk into bias, estimation, and optimization components.

We address online combinatorial optimization when the player has a prior over the adversary's sequence of losses. In this framework, Russo and Van Roy proposed an information-theoretic analysis of Thompson Sampling based on the information ratio, resulting in optimal worst-case regret bounds. In this paper we introduce…

2019-02-02abs ↗pdf ↗

We propose a paradigm to deep-learn the ever-expanding databases which have emerged in mathematical physics and particle phenomenology, as diverse as the statistics of string vacua or combinatorial and algebraic geometry. As concrete examples, we establish multi-layer neural networks as both classifiers and predictors …

2017-06-08abs ↗pdf ↗

A new method reduces both input and output dimensions for better goal-oriented analysis.

problem Simultaneous reduction of input and output dimensions for more accurate analysis.
method Coupled input-output dimension reduction, optimizing gradient-based bounds.
result Determine most informative sensors and influential parameters efficiently.

Flat surfaces that correspond to kk-differentials on compact Riemann surfaces are of finite area provided there is no pole of order kk or higher. We denote by \textit{flat surfaces with poles of higher order} those surfaces with flat structures defined by a kk-differential with at least one pole of order at least $k…

2016-06-12abs ↗pdf ↗

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.

We develop methods to efficiently approximate data in metric spaces without additional assumptions.

problem Efficiently approximating data in metric spaces without imposing structural assumptions.
method Identify discrete modulus of continuity, investigate consistency, propose algorithm, and develop approximation theory.
result Consistent approximation of data in metric spaces without structural assumptions.

New algorithms for interactive learning match minimax bounds efficiently.

problem Interactive learning in the realizable setting with computational efficiency.
method General framework, computationally efficient algorithms, Monte Carlo hit-and-run sampling.
result Sample complexities quantifiable in terms of combinatorial quantities, computationally efficient.

We view a neural network as a distributed system of which neurons can fail independently, and we evaluate its robustness in the absence of any (recovery) learning phase. We give tight bounds on the number of neurons that can fail without harming the result of a computation. To determine our bounds, we leverage the fact…

2017-06-27abs ↗pdf ↗

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.

This work generalizes bounds on the number of linear regions in CPWL NNs.

problem Determining the number of linear regions in CPWL neural networks is challenging.
method Generalized bounds on the maximal number of linear regions for arbitrary CPWL activation functions.
result Depth significantly increases the number of linear regions, but not exponentially.

Study of endperiodic maps on infinite graphs, proving homotopy and eigenvalue properties.

problem Understanding endperiodic maps on infinite graphs with finitely many ends.
method Adapting relative train track maps and combinatorial techniques to infinite type setting.
result Any generalized endperiodic map is homotopic to a relative train track map.

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.

New framework improves worst-case generalization bounds for stochastic optimization.

problem Challenges in providing generalization guarantees for stochastic optimization algorithms.
method Introduces random set stability and empirically relevant complexity measures to avoid intractable mutual information terms.
result Bounded worst-case generalization error in terms of random set stability and empirically relevant complexity measures.

Study finds conserved quantities for two types of curves on conformal sphere.

problem Identifying conserved quantities for specific types of curves on a conformal sphere.
method Used parallel tractor and Lagrangian formalism to compute conserved quantities.
result Found relation between conserved quantities of two curve types.

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.

In this paper we consider the large genus asymptotics for Masur-Veech volumes of arbitrary strata of Abelian differentials. Through a combinatorial analysis of an algorithm proposed in 2002 by Eskin-Okounkov to exactly evaluate these quantities, we show that the volume ν1(H1(m))ν_1 \big( \mathcal{H}_1 (m) \big) of a stratum i…

2018-04-15abs ↗pdf ↗

This study simplifies verification of invariants in oriented virtual knots.

problem Verifying invariants of oriented virtual knots is complex and time-consuming.
method Identifying a minimal generating set of oriented virtual Reidemeister moves.
result A four-element subset serves as a generating set for oriented virtual Reidemeister moves.

Paper proves a discrete Schwarz-Pick lemma for generalized circle packings.

problem Comparing geometric quantities of circle packings with different boundary values.
method Combinatorial Calabi flows and maximum principle.
result Discrete Schwarz-Pick lemma proven for generalized circle packings.

For triangulated surfaces, we introduce the combinatorial Calabi flow which is an analogue of smooth Calabi flow. We prove that the solution of combinatorial Calabi flow exists for all time. Moreover, the solution converges if and only if Thurston's circle packing exists. As a consequence, combinatorial Calabi flow pro…

2012-04-13abs ↗pdf ↗

New algorithm reduces semi-bandit regret using covariance estimates.

problem Complexity of semi-bandits due to joint distribution of outcomes.
method Develops a new sub-exponential distribution family and an algorithm using covariance estimates.
result Proves a new lower bound on expected regret and constructs an algorithm with asymptotic analysis.

Fractional combinatorial flow improves surface conformal structures.

problem Improving discrete conformal structures on surfaces.
method Introducing a fractional combinatorial Calabi flow for discrete conformal structures on surfaces.
result Longtime existence and global convergence of the fractional combinatorial Calabi flow for various surface types.

Polynomial-time method solves complex combinatorial semi-bandits.

problem Optimal strategies for combinatorial semi-bandits with uncorrelated Gaussian rewards.
method Proposes a polynomial-time method to solve the Graves-Lai optimization problem for various combinatorial structures.
result First known approach to implement asymptotically optimal algorithms in polynomial time for combinatorial semi-bandits.

New method finds metrics on surfaces with prescribed curvatures using circle packings and surgery.

problem Finding piecewise Euclidean metrics on surfaces with prescribed combinatorial curvatures.
method Combinatorial curvature flows with surgery for inversive distance circle packings.
result Longtime existence and global convergence of combinatorial curvature flows with surgery.

New combinatorial structure for hierarchically hyperbolic spaces.

problem Constructing new hierarchically hyperbolic spaces.
method Combinatorial hierarchical hyperbolicity criterion to construct and clarify HHS structures.
result HHSs admit a combinatorial structure, clarifying the application of the combinatorial HHS criterion.

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 ↗

A connected combinatorial 2-manifold is called degree-regular if each of its vertices have the same degree. A connected combinatorial 2-manifold is called weakly regular if it has a vertex-transitive automorphism group. Clearly, a weakly regular combinatorial 2-manifold is degree-regular and a degree-regular combinator…

2005-08-05abs ↗pdf ↗