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Tag: knowledge

  • What Is a Knowledge Graph — and Why It Matters

    What Is a Knowledge Graph — and Why It Matters How structured knowledge became healthcare’s quiet advantage The post What Is a Knowledge Graph — and Why It Matters appeared first on Towards Data Science. Steve Hedden Go to original source

  • Provable Accelerated Bayesian Optimization with Knowledge Transfer

    Provable Accelerated Bayesian Optimization with Knowledge Transfer arXiv:2511.03125v1 Announce Type: new Abstract: We study how Bayesian optimization (BO) can be accelerated on a target task with historical knowledge transferred from related source tasks. Existing works on BO with knowledge transfer either do not have theoretical guarantees or achieve the same regret as BO in the…

  • When Transformers Sing: Adapting SpectralKD for Text-Based Knowledge Distillation

    When Transformers Sing: Adapting SpectralKD for Text-Based Knowledge Distillation Exploring the frequency fingerprints of Transformers to guide smarter knowledge distillation The post When Transformers Sing: Adapting SpectralKD for Text-Based Knowledge Distillation appeared first on Towards Data Science. Ankit Singh Chauhan Go to original source

  • Build and Query Knowledge Graphs with LLMs

    Build and Query Knowledge Graphs with LLMs Knowledge Graphs are relevant A Knowledge Graph could be defined as a structured representation of information that connects concepts, entities, and their relationships in a way that mimics human understanding. It is often used to organise and integrate data from various sources, enabling machines to reason, infer, and retrieve relevant…

  • The Good-Enough Truth

    The Good-Enough Truth Could Shopify be right in requiring teams to demonstrate why AI can’t do a job before approving new human hires? Will companies that prioritize AI solutions eventually evolve into AI entities with significantly fewer employees? These are open-ended questions that have puzzled me about where such transformations might leave us in our quest for…

  • Constraint-based causal discovery with tiered background knowledge and latent variables in single or overlapping datasets

    Constraint-based causal discovery with tiered background knowledge and latent variables in single or overlapping datasets arXiv:2503.21526v1 Announce Type: new Abstract: In this paper we consider the use of tiered background knowledge within constraint based causal discovery. Our focus is on settings relaxing causal sufficiency, i.e. allowing for latent variables which may arise because relevant information…

  • What’s the point of testing machine learning model knowledge during interviews for non-research data science roles?

    What’s the point of testing machine learning model knowledge during interviews for non-research data science roles? I always make an effort to learn how a model works and how it differs from other similar models whenever I encounter a new model. So it felt natural to me that these topics were brought up in interviews.…