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.

168,657 papers · 148 categories

Trend · papers per month

201402603804 · Jun 202019922001200920172026
48 results for unbounded sets

This memoir presents a systematic study of the utility maximization problem of an investor in a constrained and unbounded financial market. Building upon the work of Hu et al. (2005) [Ann. Appl. Probab., 15, 1691--1712] in a bounded framework, we extend our analysis to the more challenging unbounded case. Our methodolo…

2017-07-01abs ↗pdf ↗

Paper solves a complex equation for unbounded convex sets.

problem Solving the LpL_p dual Minkowski problem for unbounded closed sets.
method Using variational properties of Monge-Ampère functionals, the paper proves existence, regularity, and uniqueness of solutions.
result Existence, regularity, and uniqueness of solutions to the Monge-Ampère type equation for p1p \geq 1.

We proposed the expected energy-based restricted Boltzmann machine (EE-RBM) as a discriminative RBM method for classification. Two characteristics of the EE-RBM are that the output is unbounded and that the target value of correct classification is set to a value much greater than one. In this study, by adopting featur…

2018-07-25abs ↗pdf ↗

New algorithm tackles multiclass transductive online learning with unbounded labels.

problem Characterizing optimal mistake bound for unbounded label spaces.
method Introducing new combinatorial dimensions (Level-constrained Littlestone and Branching dimensions) to characterize online learnability.
result Established trichotomy of possible minimax rates for unbounded label spaces: Θ(T)Θ(T), Θ(logT)Θ(\log T), or Θ(1)Θ(1).

New algorithms for online learning without boundedness or Lipschitz loss assumptions.

problem Online learning with unbounded domains and non-Lipschitz losses.
method Developed an algorithm with a specific regret bound and used it for saddle-point optimization.
result First algorithm achieving non-trivial dynamic regret in an unbounded domain for non-Lipschitz losses.

We study ancient solutions of polynomial growth to both continuous-time and discrete-time heat equations on graphs with unbounded Laplacians. We generalize Colding and Minicozzi's theorem [CM19] on manifolds, and the result [Hua19] on graphs with normalized Laplacians to the setting of graphs with unbounded Laplacians:…

2019-10-07abs ↗pdf ↗

Study Fourier estimator for spot volatility with unbounded coefficients and jumps.

problem Estimating spot volatility with unbounded coefficients and jumps in price process.
method Fourier estimator for spot volatility, convergence analysis for unbounded coefficients and jumps.
result Convergence of trigonometric polynomial to volatility's path, almost sure convergence of reconstructed volatility.

Advances FTPL results for bandit problems with unbounded perturbations.

problem Improving analytical foundations of FTPL in bandit problems.
method Revisiting classical FTRL-FTPL duality for unbounded perturbations.
result Establishes Best-of-Both-Worlds (BOBW) results for FTPL under a broad family of asymmetric unbounded perturbations.

Investigates optimal consumption and investment strategies in non-Markovian markets with unbounded parameters.

problem Optimal consumption and investment strategies in non-Markovian markets with unbounded parameters.
method Martingale optimal principle and quadratic BSDEs with exponential moment.
result Establishes optimal strategies for consumption and investment.

Efficiently estimates quantiles and maximum in unbounded datasets with differential privacy.

problem Efficiently estimating quantiles and maximum in unbounded datasets with differential privacy.
method Simple invocation of a subroutine called AboveThreshold, iteratively called in Sparse Vector Technique.
result Improved estimates on highest quantiles with robustness and accuracy.

Symplectic method solves infinite-dimensional Schrödinger equations.

problem Solving Schrödinger equations on infinite-dimensional Hilbert spaces with unbounded Hamiltonians.
method Analytic vectors, manifolds modelled on normed spaces, symplectic differential geometry, Marsden--Weinstein reduction.
result Mapped tt-dependent Schrödinger equations onto projective spaces.

Solves open problem on universally consistent online learning with unbounded losses.

problem Open problem on universally consistent online learning with unbounded losses.
method Constructs random measurable partitions of the instance space.
result Simple memorization rule is optimistically universal for any unbounded loss.

CRIMED optimizes regret in bandits with unbounded stochastic corruption.

problem Minimizing regret in bandits with arbitrary unbounded corruptions.
method Introduces CRIMED, an asymptotically-optimal algorithm for Gaussian distributions with known variance.
result Achieves exact lower bound on regret for Gaussian distributions with high corruption probability.

Two new algorithms improve performance in adversarial bandits with unbounded losses.

problem Adversarial Multi-Armed Bandits with unbounded losses.
method Developed UMAB-NN and UMAB-G for non-negative and general unbounded losses respectively.
result UMAB-NN achieves the first adaptive and scale-free regret bound for non-negative unbounded losses.

New PAC-Bayes bounds for unbounded losses using Cramér-Chernoff techniques.

problem Developing bounds for unbounded losses in PAC-Bayesian settings.
method Introducing a new PAC-Bayes oracle bound using Cramér-Chernoff bounds and controlling random variable tails.
result Our bounds generalize and improve upon previous results, providing more informative and potentially tighter bounds.

It is shown that the compactly supported identity component of the diffeomorphism group of the 2-dimensional punctured torus Tp2\mathbb T^2_p is an unbounded group. It follows that the fragmentation norm of Tp2\mathbb T^2_p is unbounded.

2011-03-18abs ↗pdf ↗

New inequalities for unbounded functions improve denoising score matching.

problem Statistical error bounds for denoising score matching with unbounded objective functions.
method Derive new concentration inequalities using McDiarmid's inequality and Rademacher complexity bounds.
result Improved statistical error bounds for denoising score matching.

GP-PSRL achieves sublinear regret for continuous control with unbounded state space.

problem Analyzing regret bounds for GP-PSRL in continuous control with unbounded state space.
method Recursive application of Borell-Tsirelson-Ibragimov-Sudakov inequality and chaining method.
result Sublinear regret bound of O~(HγTT)\widetilde{\mathcal{O}}(H\sqrt{γ_TT}) for GP-PSRL.

Study focal surfaces of wave fronts with unbounded curvatures.

problem Characterizing singularities of focal surfaces near non-degenerate singular points.
method Characterizations based on types of singularities and geometrical properties of initial fronts.
result Investigation of Gaussian curvature behavior of focal surfaces.

New algorithms solve stochastic variational inequalities without bounded variance assumption.

problem Solving stochastic variational inequalities without bounded variance assumption.
method Developed algorithms for two classes of problems: monotone and structured nonmonotone VIs.
result Oracle complexity of O(ε^-4) for solving VIs with unbounded domains and possibly unbounded variance.

Study shows unbounded Pontryagin numbers on curved manifolds.

problem Understanding unbounded Pontryagin numbers on curved manifolds.
method Analyzing rational linear combinations of Pontryagin numbers and their relation to the universal elliptic genus.
result Proves existence of unbounded Pontryagin numbers on nonnegatively curved spin manifolds.

New approach to concentration inequalities for unbounded state space dynamical systems.

problem Concentration inequalities for unbounded state space dynamical systems.
method Functional analytic framework, transport-entropy inequality.
result Exponential concentration inequalities for sampling from stationary distribution.

Paper tackles online control of linear systems with unbounded noise.

problem Online control of linear systems under unbounded noise with unknown convex cost functions.
method Developed an algorithm achieving ildeO(T) ilde{O}(\sqrt{T}) high-probability regret under unbounded noise, and established O(mpoly(logT)) O({ m poly} (\log T)) regret bound for strongly convex costs and sub-Gaussian noise.
result Achieved ildeO(T) ilde{O}(\sqrt{T}) high-probability regret under unbounded noise, and O(mpoly(logT)) O({ m poly} (\log T)) regret bound for specific noise and cost conditions.

Study online multiclass classification under bandit feedback, extending previous results.

problem Online multiclass classification with bandit feedback, focusing on label space unboundedness.
method Extend Daniely and Helbertal's results, show necessity and sufficiency of Bandit Littlestone dimension for learnability.
result Sequential uniform convergence is necessary but not sufficient for bandit online learnability.

New method estimates volatility for Lévy processes with unbounded jumps efficiently.

problem Efficient estimation of volatility for Lévy processes with unbounded jumps.
method Developed a new estimator based on high-order expansions of truncated moments.
result Method outperforms existing alternatives in estimating volatility.

Algorithm learns diffusion processes with high-dimensional state spaces.

problem Stochastic control of unbounded diffusion processes with high-dimensional state spaces.
method Adaptive partitioning and learning algorithm that refines discretization based on estimation bias and statistical confidence.
result Established regret bounds that depend on problem parameters, extending to unbounded diffusion processes.

New approach finds solutions to games with unbounded controls.

problem Existence of equilibrium in mean-field games with unbounded controls.
method Weak formulation and new existence/stability results for quadratic-growth generalized McKean-Vlasov BSDEs.
result Existence of equilibrium result for non-Markovian mean-field games with unbounded control space.

In this paper, we adapt stochastic Perron's method to analyze a stochastic target problem with unbounded controls in a jump diffusion set-up. With this method, we construct a viscosity sub-solution and super-solution to the associated Hamiltonian-Jacobi-Bellman (HJB) equations. Under comparison principles, uniqueness o…

2016-04-13abs ↗pdf ↗

The paper provides gradient estimates for Neumann semigroups on manifolds with boundary under unbounded curvature conditions.

problem Gradient estimates for Neumann semigroups on manifolds with boundary under unbounded curvature conditions.
method Establishes Bismut-type formulas and gradient estimates for Feynman--Kac semigroups on Riemannian manifolds with boundary, under geometric conditions formulated in terms of Ricci curvature and second fundamental form.
result Derives pointwise gradient estimates for the Neumann semigroup under variable, possibly unbounded, lower curvature bounds.

Improved sampling from Gaussian distributions with privacy constraints.

problem Sampling from unbounded Gaussian distributions with differential privacy.
method First $\widetilde{\mathcal{O}}\left(d ight)$-sample algorithm for unbounded Gaussians under $\left(\varepsilon, δ ight)$-differential privacy.
result A quadratic improvement over previous results, settling an open question.