arXiv research

Paper enhances RL policies using trust region optimization for offline data.

Most deep learning-based models for speech enhancement have mainly focused on estimating the magnitude of spectrogram while reusing the phase from noisy speech for reconstruction. This is due to the difficulty of estimating the phase of clean speech. To improve speech enhancement performance, we tackle the phase estima…

Enhances knot invariants using bilinear forms on vector spaces.

As surrogate functions of $L_0$-norm, many nonconvex penalty functions have been proposed to enhance the sparse vector recovery. It is easy to extend these nonconvex penalty functions on singular values of a matrix to enhance low-rank matrix recovery. However, different from convex optimization, solving the nonconvex l…

In this short survey article we collect the current state of the art in the nascent field of \textit{quantum enhancements}, a type of knot invariant defined by collecting values of quantum invariants of knots with colorings by various algebraic objects over the set of such colorings. This class of invariants includes c…

Enhances Transformers for better risk assessment in finance.

Enhances quantum sensing by eliminating multiple oscillations in field amplitude estimation.

This work analyzes centered binary Restricted Boltzmann Machines (RBMs) and binary Deep Boltzmann Machines (DBMs), where centering is done by subtracting offset values from visible and hidden variables. We show analytically that (i) centering results in a different but equivalent parameterization for artificial neural …

MASnet enhances speech on mobile devices with low latency.

Researchers improve imputation of missing data using diffusion transformers, quantifying uncertainty.

FuBIF enhances AD by using real-valued functions for more flexible anomaly detection.

The involutory birack counting invariant is an integer-valued invariant of unoriented tangles defined by counting homomorphisms from the fundamental involutory birack of the tangle to a finite involutory birack over a set of framings modulo the birack rank of the labeling birack. In this first of an anticipated series …

In a previous paper, the authors defined an equivariant version of the so-called Saito duality between the monodromy zeta functions as a sort of Fourier transform between the Burnside rings of an abelian group and of its group of characters. Here a so-called enhanced Burnside ring $\widehat{B}(G)$ of a finite group $G$…

Enhances data valuation by integrating global and local statistical properties.

Enhances financial market valuation and trading algorithms using distributional value functions.

GAIF enhances online multiple testing with feedback, improving statistical power.

We establish geometric and topological properties of the space of value functions in finite state-action Markov decision processes. Our main contribution is the characterization of the nature of its shape: a general polytope (Aigner et al., 2010). To demonstrate this result, we exhibit several properties of the structu…

S. Nelson, M. Orrison, V. Rivera {\cite{S}} modified Kauffman's construction of bracket. Their invariant $Φ^β_X$ takes value in a finite ring $Z_2[t]/(1+t+t^3)$. In this paper, the author generalizes this invariant. The new invariant takes value in a polynomial ring. Furthermore, for a tricolorable link diagram, the au…

Model predicts activist fund targets with 78.2% accuracy.

WLDA enhances LDA for missing data, improving classification accuracy and interpretability.

Enhances interpretability of functional survival models.

We introduce a model in which a regulator employs mechanism design to embed her human capital beta signal(s) in a firm's capital structure, in order to enhance the value of her post career change indexed executive stock option contract with the firm. We prove that the agency cost of this revolving door behavior increas…

Define quiver representation-valued invariants for classical and virtual knots

Optimizes real estate prices with dynamic strategies.

The aim of the present note is to enhance groups $G_{n}^{3}$ and to construct new invariants of classical braids. In particular, we construct invariants valued in $G_{N}^{2}$ groups. In groups $G_{n}^{2}$, the identity problem is solved, besides, their structure is much simpler than that of $G_{n}^{3}$. I am grateful t…

Finite-horizon lookahead policies are abundantly used in Reinforcement Learning and demonstrate impressive empirical success. Usually, the lookahead policies are implemented with specific planning methods such as Monte Carlo Tree Search (e.g. in AlphaZero). Referring to the planning problem as tree search, a reasonable…

Enhances insurance loss models using InsurTech data and machine learning.

E-values enhance conformal prediction methods.

Study predicts soccer player market values using machine learning and SHAP for interpretability.

LASLA improves multiple testing accuracy with network-structured data.

Enhances RL with function approximation, improving regret bounds.

We give a purely combinatorial construction of colored $\mathfrak{sl}_n$ link homology. The invariant takes values in a 2-category where 2-morphisms are given by foams, singular cobordisms between $\mathfrak{sl}_n$ webs; applying a (TQFT-like) representable functor recovers (colored) Khovanov-Rozansky homology. Novel f…

Fenrir uses probabilistic numerics to simplify solving initial value problems.

Q-SHAP efficiently calculates feature contributions in boosting trees.

New method uses DistRL to estimate entire payoff distribution for financial derivatives.

New 2-representations link spectral enhancements in link homology.

Enhanced metrics improve generative model evaluation reliability.

Stein variational gradient descent (SVGD) is a particle-based inference algorithm that leverages gradient information for efficient approximate inference. In this work, we enhance SVGD by leveraging preconditioning matrices, such as the Hessian and Fisher information matrix, to incorporate geometric information into SV…

The paper explores AI in finance, focusing on XAI's role in enhancing interpretability and trust.

E-C2ST uses E-values for high-dimensional data two-sample tests.

Enhances solar flare prediction with advanced preprocessing and contrastive learning.

Efficient method for high-dimensional American option pricing and hedging.

ICP improves text infilling and POS tagging with valid confidence sets.

Study uses Open Banking data to estimate customer value, showing potential 21% increase.

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first de…

Enhances power of covariance matrix tests for high-dimensional data.

The paper introduces ESG valuation in option pricing using binomial trees.

FE-GAN improves VaR and ES estimation in financial risk management.