Offentlig tilgang

The cost of fairness in binary classification

AK Menon, RC Williamson

Conference on Fairness, accountability and transparency, 107-118, 2018

Mandater: US Department of Defense, Australian Research Council

Learning with symmetric label noise: The importance of being unhinged

B Van Rooyen, A Menon, RC Williamson

Advances in neural information processing systems 28, 2015

Mandater: Australian Research Council

Learning from corrupted binary labels via class-probability estimation

A Menon, B Van Rooyen, CS Ong, B Williamson

International conference on machine learning, 125-134, 2015

Mandater: Australian Research Council

Fast rates in statistical and online learning

T Van Erven, P Grunwald, NA Mehta, M Reid, R Williamson

MIT Press, 2015

Mandater: Australian Research Council

Elicitation and identification of properties

I Steinwart, C Pasin, R Williamson, S Zhang

Conference on Learning Theory, 482-526, 2014

Mandater: Australian Research Council

A theory of learning with corrupted labels

B Van Rooyen, RC Williamson

Journal of Machine Learning Research 18 (228), 1-50, 2018

Mandater: Australian Research Council

Composite multiclass losses

RC Williamson, E Vernet, MD Reid

Journal of Machine Learning Research 17 (222), 1-52, 2016

Mandater: Australian Research Council

Bipartite ranking: a risk-theoretic perspective

AK Menon, RC Williamson

Journal of Machine Learning Research 17 (195), 1-102, 2016

Mandater: Australian Research Council

Pac-bayesian bound for the conditional value at risk

Z Mhammedi, B Guedj, RC Williamson

Advances in Neural Information Processing Systems 33, 17919-17930, 2020

Mandater: Australian Research Council

A loss framework for calibrated anomaly detection

AK Menon, RC Williamson

Proceedings of the 32nd international conference on neural information …, 2018

Mandater: Australian Research Council

On the consistency of output code based learning algorithms for multiclass learning problems

HG Ramaswamy, BS Babu, S Agarwal, RC Williamson

Conference on Learning Theory, 885-902, 2014

Mandater: Australian Research Council, Department of Science & Technology, India

Generalized mixability via entropic duality

MD Reid, RM Frongillo, RC Williamson, N Mehta

Conference on Learning Theory, 1501-1522, 2015

Mandater: Australian Research Council

The geometry of losses

RC Williamson

Conference on Learning Theory, 1078-1108, 2014

Mandater: Australian Research Council

Bayes-optimal scorers for bipartite ranking

AK Menon, RC Williamson

Conference on Learning Theory, 68-106, 2014

Mandater: Australian Research Council

From stochastic mixability to fast rates

NA Mehta, RC Williamson

Advances in Neural Information Processing Systems 27, 2014

Mandater: Australian Research Council

[PDF] arxiv.org

On the richness of calibration

B Höltgen, RC Williamson

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023

Mandater: German Research Foundation, Federal Ministry of Education and Research, Germany

Constant regret, generalized mixability, and mirror descent

Z Mhammedi, RC Williamson

Advances in Neural Information Processing Systems 31, 2018

Mandater: Australian Research Council

Exp-concavity of proper composite losses

P Kamalaruban, R Williamson, X Zhang

Conference on Learning Theory, 1035-1065, 2015

Mandater: Australian Research Council

Random classification noise does not defeat all convex potential boosters irrespective of model choice

Y Mansour, R Nock, R Williamson

International Conference on Machine Learning, 23706-23742, 2023

Mandater: German Research Foundation