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Tag: design

  • The Critical Horizon: Inspection Design Principles for Multi-Stage Operations and Deep Reasoning

    The Critical Horizon: Inspection Design Principles for Multi-Stage Operations and Deep Reasoning arXiv:2602.09394v1 Announce Type: new Abstract: Manufacturing lines, service journeys, supply chains, and AI reasoning chains share a common challenge: attributing a terminal outcome to the intermediate stage that caused it. We establish an information-theoretic barrier to this credit assignment problem: the signal connecting…

  • Decision-Focused Sequential Experimental Design: A Directional Uncertainty-Guided Approach

    Decision-Focused Sequential Experimental Design: A Directional Uncertainty-Guided Approach arXiv:2602.05340v1 Announce Type: new Abstract: We consider the sequential experimental design problem in the predict-then-optimize paradigm. In this paradigm, the outputs of the prediction model are used as coefficient vectors in a downstream linear optimization problem. Traditional sequential experimental design aims to control the input variables (features)…

  • How to Crack Machine Learning System-Design Interviews

    How to Crack Machine Learning System-Design Interviews A comprehensive guide into Meta, Apple, Reddit, Amazon, Google, and Snap ML design interviews The post How to Crack Machine Learning System-Design Interviews appeared first on Towards Data Science. Aliaksei Mikhailiuk Go to original source

  • Robust Experimental Design via Generalised Bayesian Inference

    Robust Experimental Design via Generalised Bayesian Inference arXiv:2511.07671v1 Announce Type: new Abstract: Bayesian optimal experimental design is a principled framework for conducting experiments that leverages Bayesian inference to quantify how much information one can expect to gain from selecting a certain design. However, accurate Bayesian inference relies on the assumption that one’s statistical model of…

  • QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design

    QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design arXiv:2410.07961v2 Announce Type: cross Abstract: Quantum computing is an emerging field recognized for the significant speedup it offers over classical computing through quantum algorithms. However, designing and implementing quantum algorithms pose challenges due to the complex nature of quantum mechanics and the necessity for precise control…

  • Stop Feeling Lost :  How to Master ML System Design

    Stop Feeling Lost :  How to Master ML System Design What machine learning system design is and how to prepare for it The post Stop Feeling Lost :  How to Master ML System Design appeared first on Towards Data Science. Egor Howell Go to original source

  • BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design

    BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design arXiv:2508.21184v1 Announce Type: cross Abstract: We propose a general-purpose approach for improving the ability of Large Language Models (LLMs) to intelligently and adaptively gather information from a user or other external source using the framework of sequential Bayesian experimental design (BED). This enables LLMs to…

  • How to Design Machine Learning Experiments — the Right Way

    How to Design Machine Learning Experiments — the Right Way The key to successful ML projects isn’t always more resources The post How to Design Machine Learning Experiments — the Right Way appeared first on Towards Data Science. TDS Editors Go to original source

  • Design Smarter Prompts and Boost Your LLM Output: Real Tricks from an AI Engineer’s Toolbox

    Design Smarter Prompts and Boost Your LLM Output: Real Tricks from an AI Engineer’s Toolbox Not just what you ask, but how you ask it. Practical techniques for prompt engineering that deliver The post Design Smarter Prompts and Boost Your LLM Output: Real Tricks from an AI Engineer’s Toolbox appeared first on Towards Data Science. Ugo Pradère…

  • Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems

    Gradient-Free Sequential Bayesian Experimental Design via Interacting Particle Systems arXiv:2504.13320v1 Announce Type: new Abstract: We introduce a gradient-free framework for Bayesian Optimal Experimental Design (BOED) in sequential settings, aimed at complex systems where gradient information is unavailable. Our method combines Ensemble Kalman Inversion (EKI) for design optimization with the Affine-Invariant Langevin Dynamics (ALDI) sampler for…

  • Dose-finding design based on level set estimation in phase I cancer clinical trials

    Dose-finding design based on level set estimation in phase I cancer clinical trials arXiv:2504.09157v1 Announce Type: new Abstract: The primary objective of phase I cancer clinical trials is to evaluate the safety of a new experimental treatment and to find the maximum tolerated dose (MTD). We show that the MTD estimation problem can be regarded…

  • Optimal Survey Design for Private Mean Estimation

    Optimal Survey Design for Private Mean Estimation arXiv:2501.18121v1 Announce Type: new Abstract: This work identifies the first privacy-aware stratified sampling scheme that minimizes the variance for general private mean estimation under the Laplace, Discrete Laplace (DLap) and Truncated-Uniform-Laplace (TuLap) mechanisms within the framework of differential privacy (DP). We view stratified sampling as a subsampling operation,…

  • Apollo and Design Choices of Video Large Multimodal Models (LMMs)

    Apollo and Design Choices of Video Large Multimodal Models (LMMs) Let’s Explore Major Design Choices from Meta’s Apollo Paper Continue reading on Towards Data Science » Matthew Gunton Go to original source

  • Design Patterns with Python for Machine Learning Engineers: Template Method

    Design Patterns with Python for Machine Learning Engineers: Template Method Learn how to use the Template design pattern to enhance your code Continue reading on Towards Data Science » Marcello Politi Go to original source

  • A Design Researcher’s Guide to Publishing

    A Design Researcher’s Guide to Publishing A Guide to Publishing Human-Computer Interaction (HCI) and Design Research Papers Turn ‘publish or perish’ into ‘learn, write, and share’ When I first started my PhD three years ago, I was very new to the world of academia and the process of publishing in journals and conferences. Coming from Computer Engineering,…

  • 170  |  Formalizing Design with Gabrielle Mérite and Alan Wilson

    170  |  Formalizing Design with Gabrielle Mérite and Alan Wilson Data design systems and styleguides are currently a huge trend in the data design world. Moritz is joined by Gabrielle Mérite and Alan Wilson and together we exchange experiences in this emerging space, from designing dataviz components as part of Adobe Spectrum, the styleguide for Deloitte’s Insights…