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Mathematics & Statistics
New mathematics and statistics is posted on arXiv, often long before it appears in a journal. This page shows the newest papers ReadSearch has read, from algebra and geometry to analysis, probability and applied mathematics.
The newest 1,000 papers, from 13 October 2026 to 5 November 2026: 971 arXiv preprints and 29 OpenAlex records.
Newest papers, page 28
Global $\mathcal{O}\left(k^{-2}\right)$ Convergence of Multilevel Gradient-Regularized Newton Methods
We develop and analyze multilevel gradient-regularized Newton methods for unconstrained convex optimization with Lipschitz-continuous Hessians.Understanding Practical Optimization in Machine Learning
Modern machine learning relies on practical optimization methods that often differ from the algorithms studied in classical analyses: they train submodels, clip or normalize gradients, use…On the asymptotic behaviour of $α$-divergence generalized posteriors
We study the asymptotic behaviour of the solutions to the unconstrained generalized variational inference problem regularized by an $α$-divergence.Measurement-dependent reduction of open dynamics in the quantum phase estimation algorithm: the visible subspace and the damped Fejér kernel
For the quantum phase estimation (QPE) algorithm we study the minimal space of observables that is sufficient to predict the entire output distribution under open dynamics of the counting register.Autonomous Structural Discovery Of Bioprocess Dynamics And Kinetics Via LLM-Driven Agents
High-fidelity digital twins in continuous biomanufacturing are often bottlenecked by incomplete kinetic models, while standard data-driven algorithms (e.g., SINDy, PINNs) lack interpretability or…A knowledge-driven nonconvex square-root regularization framework for joint group sparsity and structured smoothness
Structured sparse learning is a leading paradigm for high-dimensional data modeling, as it enables rigorous integration of domain-validated structural priors into the learning process.Differentiability and Convexity of the Solution Maps for Fully Non-linear Parabolic HJB Equations
We study the dependence on the terminal condition of solutions to a fully nonlinear parabolic Hamilton--Jacobi--Bellman (HJB) equation, when the terminal condition varies along a finite-dimensional…Benchmarking quantum-annealing-based approaches for factory layout planning
The earlystage of factory layout planning has a direct effect on the operating costs, efficiency, and productivity of manufacturing systems.Minimax Rates for Conditional Generative Learning under Wasserstein Loss
We study minimax rates for conditional generative learning under integrated Wasserstein loss, with Hölder continuous conditional laws and an unrestricted covariate distribution.Model reduction in time: Learning flow maps for reducing stochastic dynamical systems in time
Predictions with dynamical systems can be computationally expensive---even with reduced models---because reaching future prediction times can require many sequential time integration steps.Constraint Learning by Optimizing over Trained Neural Networks: A Pragmatic Tutorial
Constraint learning is an emerging paradigm of modeling optimization problems with the help of machine learning.Geometric aspects of fault tolerance
We highlight three geometric aspects of fault tolerance.KAPPA: Checking the Proofs in Statistics Papers with Lean 4 and Language Model Agents
Papers in statistical theory rest on long proofs that few readers check line by line.Proofs of strong forms of the Bovdi--Geche universality conjecture and a complex analogue
We prove two universality theorems for neural networks consisting of a single neuron.Provably Efficient Q-learning for Robust Reinforcement Learning
Standard reinforcement learning (RL) algorithms based on Markov Decision Processes (MDPs) are vulnerable to sim-to-real gaps.SCAFFOLD under Hessian Similarity: Sharp Convergence Rates
One of the main challenges of federated learning is heterogeneous data split among the clients, leading to biased local updates called client drift.Competing coherence geometries in positive maps: positivity hierarchies, atomicity, and optimal entanglement witnesses
We introduce a family of positive maps on qudits whose Choi operators combine two competing coherence patterns: independent exchange couplings and a collective set of diagonal couplings.The $\varepsilon$-smoothed Entanglement of Formation and its relation to the Moreau-Yosida approximation
We describe a family of convex continuous functions $E_{F,\varepsilon}$, $\varepsilon\in(0,1]$, on the set of states of a bipartite quantum system (consisting of finite-dimensional or…Recertifying decisions via e-closure: uniform improvements of conformal risk control and randomized e-BH
Statistical procedures often control expected loss at a prescribed level while leaving part of their risk budget unused.Complete entropy contraction from conditional hyperboundedness
For finite-dimensional quantum channels compatible with a faithful conditional expectation, we show that conditional hyperboundedness and strict GNS contraction together yield a relative entropy…
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