NEURON SHAPLEY: DISCOVERING THE RESPONSIBLE NEURONS

von Ghorbani, Amirata
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 8 of 27 (2021)

WeightedSHAP: analyzing and improving Shapley based feature attributions

von Kwon, Yongchan
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 44 of 50 (2023)

HOW TO LEARN WHEN DATA REACTS TO YOUR MODEL: PERFORMATIVE GRADIENT DESCENT

von IZZO, ZACHARY
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 6 of 16 (2022)

A DISTRIBUTIONAL FRAMEWORK FOR DATA VALUATION

von Ghorbani, Amirata
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 5 of 15 (2021)

Estimating and Explaining Model Performance When Both Covariates and Labels Shift

von Chen, Lingjiao
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 15 of 50 (2023)

Uncalibrated Models Can Improve Human-AI Collaboration

von Vodrahalli, Kailas
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 6 of 50 (2023)

Multiaccuracy: Black-Box Post-Processing for Fairness in Classification

von Kim, Michael P.
Veröffentlicht in AAAI/ACM Conference on AI, Ethics, and Society (2. : 2019 : Honolulu, Hawaii) AIES'19 (2019)

FRUGALML: HOW TO USE ML PREDICTION APIS MORE ACCURATELY AND CHEAPLY

von Chen, Lingjiao
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 13 of 27 (2021)

When and How Mixup Improves Calibration

von Zhang, Linjun
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 32 of 33 (2023)

MAKING Al FORGET YOU: DATA DELETION IN MACHINE LEARNING

von Ginart, Antonio
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 5 of 20 (2020)

Adversarial Training Helps Transfer Learning via Better Representations

von Deng, Zhun
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 30 of 36 (2022)

PREDICTING VISUO-MOTOR DISEASES FROM EYE TRACKING DATA

von Vodrahalli, Kailas
Veröffentlicht in Pacific Symposium on Biocomputing (27. : 2022 : Online) Pacific Symposium on Biocomputing 2022 (2022)

C-Mixup: Improving Generalization in Regression

von Yao, Huaxiu
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 5 of 50 (2023)

Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning

von Liang, Victor Weixin
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 23 of 50 (2023)

SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis

von Daneshjou, Roxana
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 24 of 50 (2023)

CLOUDPRED: PREDICTING PATIENT PHENOTYPES FROM SINGLE-CELL RNA-SEQ

von He, Bryan
Veröffentlicht in Pacific Symposium on Biocomputing (27. : 2022 : Online) Pacific Symposium on Biocomputing 2022 (2022)

Improving Out-Of-Distribution Robustness Via Selective Augmentation

von Yao, Huaxiu
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 31 of 33 (2023)

HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions

von Chen, Lingjiao
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 32 of 50 (2023)

MOPO: MODEL-BASED OFFLINE POLICY OPTIMIZATION

von Yu, Tianhe
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 17 of 27 (2021)

IMPROVING GENERALIZATION IN META-LEARNING VIA TASK AUGMENTATION

von YAO, HUAXIU
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 15 of 16 (2022)