Teresa Yeo

Likes dogs I am a PhD student at the VILAB, EPFL supervised by Amir Zamir and Pierre Dillenbourg. My research now is on the intersection of computer vision and machine learning. I am also interested in the theory and methods for algorithmic teaching and inverse reinforcement learning.

My undergrad was at the National University of Singapore in the Mathematics department. I went on to do my Master in Financial Engineering at Columbia University and became a quantitve analyst working on systematic strategies for equity portfolios. I then returned to school to do a Master in Machine Learning at Cambridge University.

Publications.

3D Common Corruptions and Data Augmentation

Kar, O., Yeo, T., Atanov, A., Zamir, A.

CVPR 2022 (Oral)

Using 3D information to generate real-world corruptions.

Paper     Website     Code

Robustness via Cross-Domain Ensembles

Yeo, T.*, Kar, O.*, Zamir, A.

ICCV 2021 (Oral)

Ensembling via a diverse set of middle domains.

Paper     Website     Code

Robust Learning Through Cross-Task Consistency

Zamir, A.*, Sax, A.*, Yeo, T., Kar, O., Cheerla, N., Suri, R., Cao, Z., Malik, J., Guibas, L.

Arxiv 2020, ECCV 2020 (demo)

Given a dictionary of tasks, augment the learning objective with constraints for cross-task consistency.

Paper     Website     Code

Iterative Classroom Teaching

Yeo, T., Kamalaruban, P., Singla, A., Merchant, A., Asselborn, T., Faucon, L., Dillenbourg, P., Cevher, V

AAAI 2019 (Oral), AMLD 2019 (Invited talk)

Finding the optimal sequence of examples to train a class of linear algorithms with applications to teaching to write and to classify.

Paper

Assisted Inverse Reinforcement Learning

Kamalaruban P., Devidze R., Yeo, T., Mittal T., Cevher V., Singla A.

NIPS 2018 Learning by Instruction Workshop

Finding the optimal sequence of examples to train an Inverse Reinforcement Learning agent.

Paper

Education.

  • 2017-Present

    École Polytechnique Fédérale de Lausanne
    EDIC

    PhD in Machine Learning and Computer Vision

  • 2015-2016

    Cambridge University,
    Information Engineering Division

    MPhil in Machine Learning and Machine Intelligence
    Thesis: Bayesian Optimization for Natural Language Processing

  • 2011-2012

    Columbia Univerity,
    Industrial Engineering and Operations Research Department

    MSc in Financial Engineering

  • 2007-2011

    National Univeristy of Singapore,
    Mathematics Department

    BSc (Hons) in Quantitative Finance
    Thesis: High Order Numerical Methods for Solving PDE with Optimal Stopping Times

Experience.

Contact.

first.lastname@epfl.ch
  • Somewhere in INJ, EPFL