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Tag: problem

  • The Black Box Problem: Why AI-Generated Code Stops Being Maintainable

    The Black Box Problem: Why AI-Generated Code Stops Being Maintainable Same notification system, two architectures. Unstructured generation couples everything into a single module. Structured generation decomposes into independent components with explicit, one-directional dependencies. Image by the author The post The Black Box Problem: Why AI-Generated Code Stops Being Maintainable appeared first on Towards Data Science.…

  • Stop Tuning Hyperparameters. Start Tuning Your Problem.

    Stop Tuning Hyperparameters. Start Tuning Your Problem. 80% of ML projects fail from bad problem framing, not bad models. A 5-step protocol to define the right problem before you write training code. The post Stop Tuning Hyperparameters. Start Tuning Your Problem. appeared first on Towards Data Science. Kaushik Rajan Go to original source

  • A brief note on learning problem with global perspectives

    A brief note on learning problem with global perspectives arXiv:2601.05441v1 Announce Type: new Abstract: This brief note considers the problem of learning with dynamic-optimizing principal-agent setting, in which the agents are allowed to have global perspectives about the learning process, i.e., the ability to view things according to their relative importances or in their true…

  • The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs

    The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs An optimal solution to the well-known NP-complete problem, when the input values are close enough to each other. The post The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs appeared first on Towards Data Science. Tigran Hayrapetyan Go to original…

  • Cryo-EM as a Stochastic Inverse Problem

    Cryo-EM as a Stochastic Inverse Problem arXiv:2509.05541v1 Announce Type: new Abstract: Cryo-electron microscopy (Cryo-EM) enables high-resolution imaging of biomolecules, but structural heterogeneity remains a major challenge in 3D reconstruction. Traditional methods assume a discrete set of conformations, limiting their ability to recover continuous structural variability. In this work, we formulate cryo-EM reconstruction as a stochastic…

  • The final solution of the Hitchhiker’s problem #5

    The final solution of the Hitchhiker’s problem #5 arXiv:2506.20672v1 Announce Type: new Abstract: A recent survey, nicknamed “Hitchhiker’s Guide”, J.J. Arias-Garc{i}a, R. Mesiar, and B. De Baets, A hitchhiker’s guide to quasi-copulas, Fuzzy Sets and Systems 393 (2020) 1-28, has raised the rating of quasi-copula problems in the dependence modeling community in spite of the…

  • šŸšŖšŸšŖšŸ Lessons in Decision Making from the Monty Hall Problem

    šŸšŖšŸšŖšŸ Lessons in Decision Making from the Monty Hall Problem The Monty Hall Problem is a well-known brain teaser from which we can learn important lessons in Decision Making that are useful in general and in particular for data scientists. If you are not familiar with this problem, prepare to be perplexed . If you…

  • Ivory Tower Notes: TheĀ Problem

    Ivory Tower Notes: TheĀ Problem Did you ever spend months on a Machine Learning project, only to discover you never defined the ā€œcorrectā€ problem at the start? If so, or even if not, and you are only starting with the data science or AI field, welcome to my first Ivory Tower Note, where I will address…

  • How to Tackle an Optimization Problem with Constraint Programming

    How to Tackle an Optimization Problem with Constraint Programming Case study: the travelling salesmanĀ problem TLDR Constraint Programming is a technique of choice for solving a Constraint Satisfaction Problem. In this article, we will see that it is also well suited to small to medium optimization problems. Using the well-known travelling salesman problem (TSP) as an…

  • The 80/20 problem of generative AIā€Šā€”ā€Ša UX research insight

    The 80/20 problem of generative AIā€Šā€”ā€Ša UX research insight Image byĀ author The 80/20 problem of generative AIā€Šā€”ā€Ša UX researchĀ insight When an LLM solves a task 80% correctly, that often only amounts to 20% of the userĀ value. The Pareto principle says if you solve a problem 20% through, you get 80% of the value. The opposite…

  • Reinforcement Learning for a Discrete-Time Linear-Quadratic Control Problem with an Application

    Reinforcement Learning for a Discrete-Time Linear-Quadratic Control Problem with an Application arXiv:2412.05906v1 Announce Type: new Abstract: We study the discrete-time linear-quadratic (LQ) control model using reinforcement learning (RL). Using entropy to measure the cost of exploration, we prove that the optimal feedback policy for the problem must be Gaussian type. Then, we apply the results…