mailitics

Tag: order

  • Learning Order Forest for Qualitative-Attribute Data Clustering

    Learning Order Forest for Qualitative-Attribute Data Clustering arXiv:2603.03387v1 Announce Type: new Abstract: Clustering is a fundamental approach to understanding data patterns, wherein the intuitive Euclidean distance space is commonly adopted. However, this is not the case for implicit cluster distributions reflected by qualitative attribute values, e.g., the nominal values of attributes like symptoms, marital status,…

  • Exploring Merit Order and Marginal Abatement Cost Curve in Python

    Exploring Merit Order and Marginal Abatement Cost Curve in Python To achieve the global temperature limit goals of 1.5°C by the end of the century set by the Paris Agreement, different institutions have come up with different scenarios. There is a consensus among the mitigation scenarios that the share of low-carbon technologies such as renewable energy needs…

  • On computing and the complexity of computing higher-order $U$-statistics, exactly

    On computing and the complexity of computing higher-order $U$-statistics, exactly arXiv:2508.12627v1 Announce Type: new Abstract: Higher-order $U$-statistics abound in fields such as statistics, machine learning, and computer science, but are known to be highly time-consuming to compute in practice. Despite their widespread appearance, a comprehensive study of their computational complexity is surprisingly lacking. This paper…

  • High-Order Error Bounds for Markovian LSA with Richardson-Romberg Extrapolation

    High-Order Error Bounds for Markovian LSA with Richardson-Romberg Extrapolation arXiv:2508.05570v1 Announce Type: new Abstract: In this paper, we study the bias and high-order error bounds of the Linear Stochastic Approximation (LSA) algorithm with Polyak-Ruppert (PR) averaging under Markovian noise. We focus on the version of the algorithm with constant step size $alpha$ and propose a…

  • Hess-MC2: Sequential Monte Carlo Squared using Hessian Information and Second Order Proposals

    Hess-MC2: Sequential Monte Carlo Squared using Hessian Information and Second Order Proposals arXiv:2507.07461v1 Announce Type: new Abstract: When performing Bayesian inference using Sequential Monte Carlo (SMC) methods, two considerations arise: the accuracy of the posterior approximation and computational efficiency. To address computational demands, Sequential Monte Carlo Squared (SMC$^2$) is well-suited for high-performance computing (HPC) environments.…

  • Critically-Damped Higher-Order Langevin Dynamics

    Critically-Damped Higher-Order Langevin Dynamics arXiv:2506.21741v1 Announce Type: new Abstract: Denoising Diffusion Probabilistic Models represent an entirely new class of generative AI methods that have yet to be fully explored. Critical damping has been successfully introduced in Critically-Damped Langevin Dynamics (CLD) and Critically-Damped Third-Order Langevin Dynamics (TOLD++), but has not yet been applied to dynamics of…

  • Zeroth-Order Optimization Finds Flat Minima

    Zeroth-Order Optimization Finds Flat Minima arXiv:2506.05454v1 Announce Type: cross Abstract: Zeroth-order methods are extensively used in machine learning applications where gradients are infeasible or expensive to compute, such as black-box attacks, reinforcement learning, and language model fine-tuning. Existing optimization theory focuses on convergence to an arbitrary stationary point, but less is known on the implicit…

  • Infinitesimal Higher-Order Spectral Variations in Rectangular Real Random Matrices

    Infinitesimal Higher-Order Spectral Variations in Rectangular Real Random Matrices arXiv:2506.03764v1 Announce Type: new Abstract: We present a theoretical framework for deriving the general $n$-th order Fr’echet derivatives of singular values in real rectangular matrices, by leveraging reduced resolvent operators from Kato’s analytic perturbation theory for self-adjoint operators. Deriving closed-form expressions for higher-order derivatives of singular…

  • Building a Regression Model: Delivery Duration Prediction

    Building a Regression Model: Delivery Duration Prediction Building a Regression Model to Predict Delivery Durations: A Practical Guide E2E walkthrough for approaching a regression modeling task In this article, we’re going to walk through the process of building a regression model — from dataset cleaning & preparation, to model training & evaluation. The specific regression task we will…

  • Optimize the dbt Doc Function with a CI

    Optimize the dbt Doc Function with a CI How to set an automated check to improve your dbt documentation Image by the author (generated with chatgpt) In large dbt projects, maintaining consistent and up-to-date documentation can be a challenge. Although dbt’s {{ doc() }} function allows you to store and reuse descriptions for the columns of…