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Tag: task

  • Multi-task Modeling for Engineering Applications with Sparse Data

    Multi-task Modeling for Engineering Applications with Sparse Data arXiv:2601.05910v1 Announce Type: new Abstract: Modern engineering and scientific workflows often require simultaneous predictions across related tasks and fidelity levels, where high-fidelity data is scarce and expensive, while low-fidelity data is more abundant. This paper introduces an Multi-Task Gaussian Processes (MTGP) framework tailored for engineering systems characterized…

  • Why Task-Based Evaluations Matter

    Why Task-Based Evaluations Matter This article is adapted from a lecture series I gave at Deeplearn 2025: From Prototype to Production: Evaluation Strategies for Agentic Applications. Task-based evaluations, which measure an AI system’s performance in use-case-specific, real-world settings, are underadopted and understudied. There is still an outsized focus in AI literature on foundation model benchmarks.…

  • AI Agents Are Shaping the Future of Work Task by Task, Not Job by Job

    AI Agents Are Shaping the Future of Work Task by Task, Not Job by Job What two groundbreaking studies reveal about the future of human-AI collaboration, and the enterprise playbook for thriving in the AI agent era The post AI Agents Are Shaping the Future of Work Task by Task, Not Job by Job appeared…

  • GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds

    GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds arXiv:2505.02972v1 Announce Type: new Abstract: Multi-Task Learning (MTL) seeks to boost statistical power and learning efficiency by discovering structure shared across related tasks. State-of-the-art MTL representation methods, however, usually treat the latent representation matrix as a point in ordinary Euclidean space, ignoring its often non-Euclidean geometry, thus…

  • Task Shift: From Classification to Regression in Overparameterized Linear Models

    Task Shift: From Classification to Regression in Overparameterized Linear Models arXiv:2502.13285v1 Announce Type: new Abstract: Modern machine learning methods have recently demonstrated remarkable capability to generalize under task shift, where latent knowledge is transferred to a different, often more difficult, task under a similar data distribution. We investigate this phenomenon in an overparameterized linear regression…