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298 papers, from 31 August 2026 to 5 November 2026: 270 arXiv preprints and 28 OpenAlex records.
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Newest papers, page 14
Rank-1-perturbed trickledown theorems: Mixing time of Glauber dynamics for the Sherrington-Kirkpatrick model up to $β\leq \frac{1}{2}+\varepsilon$
We introduce a new family of trickledown theorems, a.k.a., local to global technique to bound the spectral gap of the Glauber dynamics for multi-state spin systems.Stochastic Gradient Descent over P2
Stochastic gradient descent (SGD) admits diffusion approximations that replace the complicated randomness of stochastic gradients by Gaussian noise, providing a powerful tool for understanding its…Closed-form estimation of the exponential scale under two-sided informative random censorship
We estimate the scale of an exponential lifetime from observations censored randomly from both sides, under an informative model in which each censoring law is a power of the lifetime survival…Short-maturity skew stickiness ratio under local volatility
We prove that the skew stickiness ratio converges to two at short maturity under local volatility models.Generalization Analysis of Distributed Kernel-based Robust Gradient Descent Algorithms
In this paper, we investigate the generalization performance of distributed gradient descent algorithms in a reproducing kernel Hilbert space under a robust loss function $l_σ$.Free-Probabilistic State Evolution and Random Matrix Discrepancy
Let $A_1,\ldots,A_n$ be independent $d \times d$ real symmetric Gaussian random matrices, and consider the linear operator $A(x) = n^{-1/2}\sum_{i=1}^n x_i A_i$, $x\in \mathbb{R}^n$.Score-based Outlier Generation via Controlling the Radon-Nikodym Derivative
Outliers are important for stress-testing algorithms and understanding system behaviour under rare conditions.Almost Sure Convergence Analysis of Stochastic Gradient Methods with Clipping and Additive Noise
Stochastic gradient descent (SGD) with gradient clipping and additive noise has become a standard technique for training machine learning models, particularly in applications requiring robustness or…Near-Gaussian counterexamples to the Ball-Nayar-Tkocz entropy concavity conjecture
The Ball-Nayar-Tkocz conjecture asserts that, for independent real random variables $X,Y$ with a common log-concave density, the function $t\mapsto h(\sqrt tX+\sqrt{1-t}Y)$ is concave on $[0,1]$.High-probability guarantees for linear accessibility in feature superposition
Neural networks can leverage feature superposition to encode more concepts than dimensions, but cross-feature interference constrains the linear accessibility of simultaneously active features.Variance-Optimal Hedging in the Rough Hawkes--Heston Model
We study variance-optimal stock hedging and the convergence of approximate strategies in the rough Hawkes--Heston model.High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression
Sparsity is a powerful structural resource in optimization and statistics.Tensor Network Moral Graph Recovery of Discrete Probability Distributions
We present a method for recovering the moral graph of a causal DAG from a probability distribution over discrete variables, using fully connected tensor networks (FCTNs) with…Gaussian Approximation for Multivariate Martingale Sums from Uniformly Ergodic Markov Chains
We develop Gaussian approximation bounds in higher-order Wasserstein distance $W_p$, $p\geq2$, for sums of multivariate martingale differences generated by a uniformly ergodic Markov chain.Entropy bounds and global couplings for union-closed families
We give a computer-assisted proof that every finite union-closed family containing a nonempty set has an element in at least 0.38288525 of its members.Learning Adaptive SED for heterogeneous load balancing
We study a two-server load balancing system with heterogeneous service rates that are a priori unknown to the dispatcher.Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler
We study the problem of sampling from $μ(\mathrm{d}x)\propto e^{-V(x)}\,\mathrm{d}x$ on $\mathbb{R}^d$, where $V$ is $α$-strongly convex and $β$-smooth, and write $κ:=β/α$.Almost Sharp Equivalence between Approximate Message Passing and Low-Degree Polynomials
We prove a sharp lower bound for growing-degree polynomial estimation in the Gaussian planted submatrix model.Pricing and Hedging of Discretely Monitored Asian Options in the Volterra-Heston Model
We develop semi-closed pricing formulas and lifted-model hedging methods for discretely monitored geometric and arithmetic Asian options in the Volterra-Heston stochastic volatility model.Fixed Points for the $q$-Bass Martingale: Existence, Stability, and Convergence
We establish existence, uniqueness, stability, and convergence results for one-dimensional $q$-Bass martingales, characterized as the martingales with prescribed initial and terminal marginals whose…