24 citations · 83 across the 32 of their papers we have counts for
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cs.LG2023★ 2 cited
Reasonable Scale Machine Learning with Open-Source Metaflow
Jacopo Tagliabue, Hugo Bowne-Anderson, Ville Tuulos +3
As Machine Learning (ML) gains adoption across industries and new use cases, practitioners increasingly realize the challenges around effectively developing and iterating on ML sys…
cs.LG2021★ 8 cited
You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stack
Jacopo Tagliabue
We argue that immature data pipelines are preventing a large portion of industry practitioners from leveraging the latest research on recommender systems. We propose our template d…
cs.LG2020★ 3 cited
Blending Search and Discovery: Tag-Based Query Refinement with Contextual Reinforcement Learning
Bingqing Yu, Jacopo Tagliabue
We tackle tag-based query refinement as a mobile-friendly alternative to standard facet search. We approach the inference challenge with reinforcement learning, and propose a deep…