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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.

168,695 papers · 148 categories

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4182123164 · Jun 202019922001200920172026
48 results for log-barrier potential

Study explores algorithmic collusion in repeated games using various learning dynamics.

problem Understanding algorithmic collusion in repeated games with different learning dynamics.
method Examines QQ-learning, gradient learning, and other dynamics in a general repeated game setting.
result Characterizes the set of payoff vectors achievable by these dynamics, revealing possibilities for collusion.

Improves policy optimization with polylog(T) regret bounds for stochastic losses.

problem Improves theoretical guarantees for policy optimization in stochastic settings.
method Leverages Tsallis and Shannon entropy regularizers for polylog(T) regret, and log-barrier regularizer for adversarial settings.
result Achieves a first-order polylog(T) regret bound for policy optimization in stochastic settings.

A scalable framework optimizes multi-asset portfolios with constraints.

problem Optimizing multi-asset portfolios with inequality constraints.
method Integrates neural policies with Pontryagin's Maximum Principle, enforcing feasibility via log-barrier regularization.
result Recover KKT-optimal policies in high-dimensional problems without violating constraints.

Safe-M3^3-UCRL learns safe policies for multi-agent systems with global constraints.

problem Global constraints in mean-field reinforcement learning for multi-agent systems.
method Safe-M3^3-UCRL uses epistemic uncertainty and log-barrier approach to ensure constraints satisfaction.
result Safe-M3^3-UCRL learns safe policies for multi-agent systems with global constraints.

New algorithm reduces prediction errors across various loss functions.

problem Online forecasting algorithms' inability to adapt to different loss functions.
method Design of a novel Follow-the-Perturbed-Leader (FTPL) algorithm with self-concordant noise.
result Simultaneously achieves ildeO(T) ilde O(\sqrt{T}) regret for bounded proper losses and O(logT)O(\log T) regret for bounded smooth proper losses.

Improved regret bound for adversarial MDPs with linear function approximation.

problem Learning in adversarial MDPs with changing loss functions and large state spaces.
method Two algorithms: refined FTRL with log-barrier regularizer and magnitude-reduced loss estimator.
result Achieved ildeO(K) ilde{\mathcal O}(\sqrt K) regret, improving over ildeO(K2/3) ilde{\mathcal O}(K^{2/3}).

New bounds for online portfolio selection without smoothness assumptions.

problem Online portfolio selection with non-Lipschitz, non-smooth losses.
method Data-dependent bounds using novel smoothness characterizations and FTRL with self-concordant regularizers.
result Achieves logarithmic regrets when data is 'easy' and sublinear worst-case regrets.

New method improves generative modeling on convex domains using regularized mirror maps and Student-t priors.

problem Challenges in generative modeling on convex domains with heavy-tailed targets.
method Mirror Flow Matching with regularized mirror maps and Student-t priors.
result Empirically outperforms baselines and achieves competitive sample quality.

New algorithms handle phase retrieval with rank d measurements, revealing phase transitions.

problem Phase retrieval with rank d measurements.
method Random duality theory (RDT) and descending phase retrieval algorithms (dPR).
result Minimal sample complexity ratio for dPR's success exhibits phase transitions.

New algorithm reduces regret in online portfolio and quantum state learning.

problem Efficiently learning portfolios and quantum states online with minimal regret.
method BISONS algorithm for online portfolio selection, SCHRODINGER'S BISONS for quantum states, with polylogarithmic regret.
result First efficient algorithm with polylogarithmic regret for online portfolio selection and quantum states.

Develops a deep non-stationary kernel for non-stationary spatio-temporal point processes.

problem Capturing non-stationary dependencies in point process data.
method Approximates the influence kernel with a novel low-rank decomposition and introduces a log-barrier penalty to maintain non-negativity.
result Demonstrates superior performance and computational efficiency compared to state-of-the-art methods.

We develop a novel and generic algorithm for the adversarial multi-armed bandit problem (or more generally the combinatorial semi-bandit problem). When instantiated differently, our algorithm achieves various new data-dependent regret bounds improving previous work. Examples include: 1) a regret bound depending on the …

2018-01-10abs ↗pdf ↗

RHMC improves sampling polytopes defined by inequalities with barriers.

problem Sampling polytopes defined by inequalities efficiently.
method Riemannian Hamiltonian Monte Carlo (RHMC) with a hybrid of Lewis weights and logarithmic barriers.
result RHMC achieves mixing rate of ildeO(m1/3n4/3) ilde O(m^{1/3}n^{4/3}) for polytopes defined by mm inequalities in Rn\R^n.

New algorithms reduce regret in online MDPs by adapting to data and variance.

problem Adapting to both adversarial and stochastic environments in online MDPs.
method Develops algorithms based on global optimization and policy optimization, using optimistic follow-the-regularized-leader with log-barrier regularization.
result Achieves refined data-dependent and variance-dependent regret bounds.

A new sampling method for log-concave distributions with warm starts and barriers.

problem Sampling from log-concave distributions constrained by convex bodies with barriers.
method Robust sampling framework using spectral approximations to Hessian of barrier functions.
result Improved mixing times for polytopes and spectrahedra, faster than previous methods.

In this article we discuss the distribution of asset price movements by the market potential function. From the principle of free energy minimization we analyze two different kinds of market potentials. We obtain a U-shaped potential when market reversion (i.e. contrarian investors) is dominant. On the other hand, if t…

2014-03-13abs ↗pdf ↗

Develops potential theory for WZW equation in Kähler potentials space.

problem Solving the Wess--Zumino--Witten equation in Kähler potentials.
method Introduces ωω-harmonicity on graphs to characterize the WZW equation and uses subharmonic distance.
result Shows solvability of Dirichlet problem and approximation by finite-dimensional maps.

The paper examines stability of harmonic and symphonic maps with forms and potentials.

problem Stability of harmonic and symphonic maps with forms and potentials.
method Analyzes stability of F F -harmonic and F F -symphonic maps with forms and potentials.
result Stability conditions for harmonic and symphonic maps are established.

The paper examines stability of subelliptic harmonic maps with potential.

problem Stability of subelliptic harmonic maps with potential.
method Derived first and second variation formulas, proved stability conditions, and gave instability results.
result Subelliptic harmonic maps with potential are stable under certain curvature and potential conditions.

A hyperKähler potential is a function rho that is a Kähler potential for each complex structure compatible with the hyperKähler structure. Nilpotent orbits in a complex simple Lie algebra are known to carry hyperKähler metrics admitting such potentials. In this paper, we explicitly calculate the hyperKähler potential w…

2000-01-05abs ↗pdf ↗

We consider the problem of learning an interpretable potential energy function from a Hamiltonian system's trajectories. We address this problem for classical, separable Hamiltonian systems. Our approach first constructs a neural network model of the potential and then applies an equation discovery technique to extract…

2019-07-26abs ↗pdf ↗

Article provides Bernstein gradient estimates for heat equations with potential terms.

problem Gradient estimates for heat equations with potential terms on weighted Riemannian manifolds.
method Derived Bernstein type gradient estimates for two systems of heat equations with linear, exponential, and combined potentials.
result Resolves part of the problem raised by Bhattacharyya et al. in \cite{SB-1}.

In this paper we study potential function of gradient steady Ricci solitons. We prove that infimum of potential function decays linearly; in particular, potential function of rectifiable gradient steady Ricci solitons decays linearly. As a consequence, we show that a gradient steady Ricci soliton with bounded potential…

2011-02-15abs ↗pdf ↗

We consider the geodesic equation for the generalized Kahler potential with only mixed second derivatives bounded. We show that given such two generalized Kahler potentials, there is a unique geodesic segment such that for each point on the geodesic, the generalized Kahler potential has uniformly bounded mixed second d…

2012-08-05abs ↗pdf ↗

We show two results about the Conway potential function which is known as the normalized multivariable Alexander polynomial. We first show that the Conway potential function introduced by Kauffman in "Formal Knot Theory" is indeed a link invariant. Next we show that Kauffman's potential function equals Hartley's potent…

2011-03-12abs ↗pdf ↗

The paper characterizes potential functions whose level sets are orbits in mechanical systems.

problem Characterizing smooth potential energy functions on the plane with specific level set properties.
method Analyzing inverse curvature flow and properties of level sets.
result Analytic or functions with totally path-disconnected critical sets must be radial, while every compact convex set is a critical set of a Levi potential.

The paper studies mm-quasi Einstein manifolds with convex potential and finds constant scalar curvature.

problem Investigating mm-quasi Einstein manifolds with a convex potential function.
method Analyzing integral conditions and properties of the potential vector field.
result An mm-quasi Einstein manifold with a convex potential function has constant scalar curvature.

Estimates classical potential from stock price data using quantum mechanics.

problem Estimating classical potential from empirical stock price data.
method Quantum mechanical model of stock price distribution, estimating potential from wave function.
result Suggests methods to evaluate classical potential for Schrodinger equation.

Paper connects AJ conjecture and colored Jones polynomial potential function.

problem Relationship between AA-polynomial and colored Jones polynomial.
method Connects AJ conjecture and colored Jones polynomial potential function.
result Establishes connection between AA-polynomial and colored Jones polynomial potential function.

It is known that nilpotent orbits in a complex simple Lie algebra admit hyperKähler metrics with a single function that is a global potential for each of the Kähler structures (a hyperKähler potential). In an earlier paper the authors showed that nilpotent orbits in classical Lie algebras can be constructed as finite-d…

2000-01-05abs ↗pdf ↗

We apply the potential force estimation method to artificial time series of market price produced by a deterministic dealer model. We find that dealers' feedback of linear prediction of market price based on the latest mean price changes plays the central role in the market's potential force. When markets are dominated…

2007-10-09abs ↗pdf ↗

Study classifies static potentials on 3-manifolds, proving one-dimensionality under specific conditions.

problem Classifying the dimension of static potentials on 3-manifolds.
method Analysis of relative zero sets of static potentials, using Miao and Tam's technique.
result Proves one-dimensionality of static potentials under specific conditions.

Study of metrics on positive-definite matrices from power potential, linking to power means.

problem Understanding metrics on positive-definite matrices derived from power potential.
method Explicit expressions for geodesics and distance function derived from Hessian of power potential.
result Geodesics and distance function converge to weighted matrix geometric mean as β tends to zero.

We study the influence of an additional scalar potential on various geometric and analytic properties of Dirac-harmonic maps. We will create a mathematical wish list of the possible benefits from inducing the potential term and point out that the latter cannot be achieved in general. Finally, we focus on several potent…

2019-12-04abs ↗pdf ↗

PO-Flow models potential and counterfactual outcomes for personalized treatment decisions.

problem Predicting individualized treatment effects from observational data.
method Continuous normalizing flow (CNF) framework for causal inference.
result Unified approach to potential outcome prediction, treatment effect estimation, and counterfactual prediction.