DECISION-MAKING UNDER SELECTIVE LABELS: OPTIMAL FINITE-DOMAIN POLICIES AND BEYOND

von WEI, DENNIS
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 14 of 16 (2022)

DAGS WITH NO FEARS: A CLOSER LOOK AT CONTINUOUS OPTIMIZATION FOR LEARNING BAYESIAN NETWORKS

von Wei, Dennis
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 5 of 27 (2021)

CONDITIONALLY INDEPENDENT DATA GENERATION

von Ahuja, Kartik
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (37. : 2021 : Online) 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) ; Part 3 of 3 (2022)

On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach

von Wei, Dennis
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 13 of 50 (2023)

CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions

von Puri, Isha
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 26 of 36 (2022)

IS THERE A TRADE-OFF BETWEEN FAIRNESS AND ACCURACY? A PERSPECTIVE USING MISMATCHED HYPOTHESIS TESTING

von Dutta, Sanghamitra
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 4 of 15 (2021)

Fair Transfer Learning with Missing Protected Attributes

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

TED: Teaching AI to Explain its Decisions

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