8 citations · 16 across the 12 of their papers we have counts for
4 papers · 1 filter
Conformal Prediction Sets Can Cause Disparate Impact
Jesse C. Cresswell, Bhargava Kumar, Yi Sui +1
Conformal prediction is a statistically rigorous method for quantifying uncertainty in models by having them output sets of predictions, with larger sets indicating more uncertaint…
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks
Antoni Kowalczuk, Jan Dubiński, Atiyeh Ashari Ghomi +6
Large-scale vision models have become integral in many applications due to their unprecedented performance and versatility across downstream tasks. However, the robustness of these…
Tabular Data Contrastive Learning via Class-Conditioned and Feature-Correlation Based Augmentation
Wei Cui, Rasa Hosseinzadeh, Junwei Ma +3
Contrastive learning is a model pre-training technique by first creating similar views of the original data, and then encouraging the data and its corresponding views to be close i…
Conformal Prediction Sets Improve Human Decision Making
Jesse C. Cresswell, Yi Sui, Bhargava Kumar +1
In response to everyday queries, humans explicitly signal uncertainty and offer alternative answers when they are unsure. Machine learning models that output calibrated prediction…