Javni dostop

The cost of fairness in binary classification

AK Menon, RC Williamson

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

Zahteve: 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

Zahteve: 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

Zahteve: Australian Research Council

Fast rates in statistical and online learning

T Van Erven, PD Grünwald, NA Mehta, MD Reid, RC Williamson

The Journal of Machine Learning Research 16 (1), 1793-1861, 2015

Zahteve: 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

Zahteve: Australian Research Council

Elicitation and identification of properties

I Steinwart, C Pasin, R Williamson, S Zhang

Conference on Learning Theory, 482-526, 2014

Zahteve: Australian Research Council

Composite multiclass losses

RC Williamson, E Vernet, MD Reid

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

Zahteve: Australian Research Council

Bipartite ranking: a risk-theoretic perspective

AK Menon, RC Williamson

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

Zahteve: 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

Zahteve: Australian Research Council

A loss framework for calibrated anomaly detection

AK Menon, RC Williamson

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

Zahteve: 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

Zahteve: 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

Zahteve: Australian Research Council

The geometry of losses

RC Williamson

Conference on Learning Theory, 1078-1108, 2014

Zahteve: Australian Research Council

Bayes-optimal scorers for bipartite ranking

AK Menon, RC Williamson

Conference on Learning Theory, 68-106, 2014

Zahteve: Australian Research Council

From stochastic mixability to fast rates

NA Mehta, RC Williamson

Advances in Neural Information Processing Systems 27, 2014

Zahteve: Australian Research Council

Risk measures and upper probabilities: Coherence and stratification

C Fröhlich, RC Williamson

Journal of Machine Learning Research 25 (207), 1-100, 2024

Zahteve: German Research Foundation

[PDF] arxiv.org

On the richness of calibration

B Höltgen, RC Williamson

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

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

Information processing equalities and the information–risk bridge

RC Williamson, Z Cranko

Journal of Machine Learning Research 25 (103), 1-53, 2024

Zahteve: German Research Foundation

The geometry and calculus of losses

RC Williamson, Z Cranko

Journal of Machine Learning Research 24 (342), 1-72, 2023

Zahteve: German Research Foundation