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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.

168,742 papers · 148 categories

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48 results for continuous value

Study on 2-valued dynamics on complex plane, showing some dynamics can't be group actions.

problem Whether 2-valued dynamics can be defined by the action of a 2-valued group.
method Construction of examples of dynamics that are or are not group actions.
result Some 2-valued dynamics on complex plane cannot be defined by the action of a 2-valued group.

Study shows financial value of weak information converges in discrete vs continuous markets.

problem Analyzing financial value of weak information in discrete vs continuous markets.
method Defined minimal probability measure and financial value of weak information, then showed convergence.
result Financial value of weak information converges in discrete vs continuous markets.

New model learning objective improves continuous control tasks.

problem Challenges in solving continuous control tasks using model-based reinforcement learning.
method Derived a novel value-aware model learning objective and identified and addressed stale value estimates issue.
result Value-aware objectives can be successfully deployed in solving continuous control tasks without tuning hyper-parameters.

Revisits superhedging under proportional costs in continuous time markets.

problem Superhedging in markets with proportional transaction costs.
method Set-valued stochastic analysis, continuous trading schemes, dynamic risk measure.
result Dynamic set-valued risk measure with multi-portfolio time-consistency.

Method bounds continuous-valued treatment effects when confounding variables are hidden.

problem Inferring causal effects of continuous treatments when hidden confounders are present.
method Novel methodology to bound average and conditional average continuous-valued treatment effects.
result Method gives tighter coverage of true dose-response curve than existing methods.

Researchers develop neural networks for approximating functions in Banach spaces.

problem Approximating Banach space valued continuous functions.
method Quasi-interpolation Banach space valued neural network operators using algebraic sigmoid functions.
result Jackson type inequalities for function approximation.

Classifies contravariant matrix-valued valuations on polytopes without continuity assumptions.

problem Classifying contravariant matrix-valued valuations on polytopes without continuity assumptions.
method Complete classification of contravariant matrix-valued valuations on polytopes in Rn\mathbb{R}^n without continuity assumptions.
result The only such valuation is the general Lutwak-Yang-Zhang matrix in dimension n4n \geq 4, and a new function in dimension 3.

This work takes up the challenges of utility maximization problem when the market is indivisible and the transaction costs are included. First there is a so-called solvency region given by the minimum margin requirement in the problem formulation. Then the associated utility maximization is formulated as an optimal swi…

2010-03-15abs ↗pdf ↗

Unified Bayesian Optimisation for mixed variables improves performance.

problem Efficient optimisation of problems with both categorical and continuous variables.
method Derive value proposals from the Expected Improvement criterion to optimise both categorical and continuous variables under a single acquisition metric.
result Unified approach significantly outperforms existing methods across mixed-variable tasks.

The paper uses regression trees/random forests to price Bermudan options more efficiently.

problem Pricing Bermudan options with conditional expectation estimation.
method Estimates conditional expectations using regression trees or random forests instead of traditional regression methods.
result Regression trees/random forests provide better results in high dimensions.

New algorithm learns value and advantage functions for continuous-time Markov processes without structural assumptions.

problem Learning value and advantage functions for continuous-time Markov processes without structural assumptions.
method Proposes Sobolev-prox fitted qq-learning algorithm based on Hilbert-space positive definiteness and boundedness properties of Bellman operators.
result Identifies ellipticity as a key structural property enabling reinforcement learning for Markov diffusions.

In this paper, we consider the problem of black box continuous submodular maximization where we only have access to the function values and no information about the derivatives is provided. For a monotone and continuous DR-submodular function, and subject to a bounded convex body constraint, we propose Black-box Contin…

2019-01-28abs ↗pdf ↗

Efficient optimisation of black-box problems that comprise both continuous and categorical inputs is important, yet poses significant challenges. We propose a new approach, Continuous and Categorical Bayesian Optimisation (CoCaBO), which combines the strengths of multi-armed bandits and Bayesian optimisation to select …

2019-06-20abs ↗pdf ↗

The paper improves energy decay estimates for Dir-stationary Q-valued functions and applies them to Liouville-type theorems and continuity.

problem Improving energy decay estimates for Dir-stationary Q-valued functions.
method Establishing improved decay estimates and applying them to derive Liouville-type theorems and continuity.
result Dir-stationary Q-valued functions exhibit the Lebesgue property and reside in a generalized Campanato-Morrey space.

The paper extends consistency results for sequential design strategies to vector-valued Gaussian processes.

problem Estimating excursion sets of vector-valued Gaussian processes.
method Clarifying the connection between continuous Gaussian processes and Gaussian measures in Banach spaces, extending concepts and properties from scalar-valued settings to vector-valued settings.
result Consistency results for sequential design strategies can be applied to vector-valued Gaussian processes.

Solves complex equation for specific geometric solitons.

problem Solving complex Monge-Ampère equation for specific geometric solitons.
method Aubin continuity path and continuity method.
result Initial value of the path parameter has a solution and is open to all.

Paper tackles RL with continuous actions and unmeasured confounders.

problem Offline policy learning with continuous actions and unmeasured confounders.
method Developed a novel identification result and a minimax estimator for nonparametric policy value estimation.
result Introduced a policy-gradient-based algorithm to identify the optimal policy.

A new method for interpreting AI models using Shapley value for functional data.

problem Interpreting AI models, especially those based on functional data.
method Proposes an interpretability method based on the Shapley value for continuous games.
result Demonstrates the effectiveness of the method through experiments with simulated and real data.

Paper proposes a new method to select memory data for online class-incremental learning.

problem Selecting which buffered images to replay for online class-incremental learning.
method Adversarial Shapley value scoring method to preserve latent decision boundaries.
result Proposed ASER method provides competitive or improved performance compared to state-of-the-art methods.

Despite recent successes in Reinforcement Learning, value-based methods often suffer from high variance hindering performance. In this paper, we illustrate this in a continuous control setting where state of the art methods perform poorly whenever sensor noise is introduced. To overcome this issue, we introduce Recurre…

2019-05-23abs ↗pdf ↗

Continuity of roots of hyperbolic polynomials with smooth coefficients.

problem Continuity of the solution map for hyperbolic polynomials.
method Proving continuity of the solution map from hyperbolic polynomials of degree d with C^d coefficients to their increasingly ordered roots.
result Continuity of the solution map for hyperbolic polynomials with C^d coefficients.

We study an optimal execution problem in a continuous-time market model that considers market impact. We formulate the problem as a stochastic control problem and investigate properties of the corresponding value function. We find that right-continuity at the time origin is associated with the strength of market impact…

2009-07-20abs ↗pdf ↗

A new approach to continuous-time universal portfolios using pathwise Itô calculus.

problem Continuous-time version of Cover's universal portfolio strategies.
method Pathwise Itô calculus approach to establish existence and properties of universal portfolio strategies.
result The universal portfolio strategy's portfolio value process is the average of all values of constant rebalanced strategies.

Develops scalable methods to assess sensitivity and uncertainty in continuous treatment effects.

problem Estimating effects of continuous-valued interventions from observational data, especially when ignorability and positivity assumptions are violated.
method Continuous treatment-effect marginal sensitivity model (CMSM), scalable algorithm, uncertainty-aware deep models.
result Derives bounds that agree with observed data and a defined level of hidden confounding.
Money and Goldstone modescond-mat.stat-mech

Why is ``worthless'' fiat money generally accepted as payment for goods and services? In equilibrium theory, the value of money is generally not determined: the number of equations is one less than the number of unknowns, so only relative prices are determined. In the language of mathematics, the equations are ``homoge…

2000-09-19abs ↗pdf ↗

New method decomposes profits and losses continuously, avoiding discrete reporting issues.

problem Analyzing profits and losses at discrete dates ignores detailed paths.
method Constructs a large class of continuous-time decompositions using extended Itô's formula.
result Identifies a preferred decomposition from exactness, symmetry, and normalization axioms.

Study uses actor-critic method for continuous-time mean-field control with entropy regularisation.

problem Continuous-time mean-field control in reinforcement learning.
method Actor-critic approach with entropy regularisation, value function alternation, and Wasserstein space parametrisation.
result Derives exact parametrisation of actor and critic functions in linear-quadratic mean-field framework.
The Dynamics of Moneycond-mat.stat-mech

We present a dynamical many-body theory of money in which the value of money is a time dependent ``strategic variable'' that is chosen by the individual agents. The value of money in equilibrium is not fixed by the equations, and thus represents a continuous symmetry. The dynamics breaks this continuous symmetry by fix…

1998-11-06abs ↗pdf ↗

In this paper we establish the basic tools to develop the "Calculus" associated with group-valued continuously Pansu differentiable mappings. We develop the technical machinery on which all of our results rely. In particular, the linearization of addends appearing in the Baker-Campbell-Hausdorff formula is one of the m…

2007-01-11abs ↗pdf ↗

Introduces CHL, a new loss function for continuous similarity learning.

problem Binary similarity learning limitations.
method CHL is a novel loss function that generalizes histogram loss to continuous similarities.
result CHL solves a wider range of tasks including similarity learning, representation learning, and data visualization.