Blog(1)

• Website Clustering via Transformer Context Models

  Individual characteristics as age, gender etc. are often relevant features in tasks such as lifetime value or uplift modelling. Those variables are sufficiently good in describing some high-level heuristics about a population.

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Publications(19)

• LIFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning

  AuthorMinyoung Kim, Timothy Hospedales

  PublishedInternational Conference on Learning Representation (ICLR)

  Date2025-04-25

• Principled and Efficient Motif Finding for Structure Learning in Lifted Graphical Models

  AuthorEfthymia Tsamoura

  PublishedConference on Artificial Intelligence (AAAI)

  Date2023-02-03

• From Keypoints to Object Landmarks via Self-Training Correspondence: A novel approach to Unsupervised Landmark Discovery

  AuthorEnrique Sanchez, Georgios Tzimiropoulos

  PublishedIEEE Transactions on Pattern Analysis and Machine Intelligence

  Date2023-01-04

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• [Blog] Website Clustering via Transformer Context Models

  Individual characteristics as age, gender etc. are often relevant features in tasks such as lifetime value or uplift modelling. Those variables are sufficiently good in describing some high-level heuristics about a population.

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