most citedMind the Nuisance: Gaussian Process Classification using Privileged Noise

19 citations · 45 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20223 cited

Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control

Michail Christos Doukas, Evangelos Ververas, Viktoriia Sharmanska +1

We present Free-HeadGAN, a person-generic neural talking head synthesis system. We show that modeling faces with sparse 3D facial landmarks are sufficient for achieving state-of-th…

cs.CV2022

RealPatch: A Statistical Matching Framework for Model Patching with Real Samples

Sara Romiti, Christopher Inskip, Viktoriia Sharmanska +1

Machine learning classifiers are typically trained to minimise the average error across a dataset. Unfortunately, in practice, this process often exploits spurious correlations cau…

stat.ML20145 cited

Curriculum Learning of Multiple Tasks

Anastasia Pentina, Viktoriia Sharmanska, Christoph H. Lampert

Sharing information between multiple tasks enables algorithms to achieve good generalization performance even from small amounts of training data. However, in a realistic scenario…

cs.CV201418 cited

Learning to Transfer Privileged Information

Viktoriia Sharmanska, Novi Quadrianto, Christoph H. Lampert

We introduce a learning framework called learning using privileged information (LUPI) to the computer vision field. We focus on the prototypical computer vision problem of teaching…

stat.ML201419 cited

Mind the Nuisance: Gaussian Process Classification using Privileged Noise

Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting +2

The learning with privileged information setting has recently attracted a lot of attention within the machine learning community, as it allows the integration of additional knowled…