| Nome |
# |
|
Factual and Counterfactual Explanations for Black Box Decision Making, file e0d6c930-727a-fcf8-e053-d805fe0aa794
|
817
|
|
Educational ecosystems for Information Science: the case of the University of Pisa, file e0d6c92e-2b64-fcf8-e053-d805fe0aa794
|
419
|
|
null, file e0d6c929-ec91-fcf8-e053-d805fe0aa794
|
213
|
|
A survey of methods for explaining black box models, file e0d6c92b-20c0-fcf8-e053-d805fe0aa794
|
204
|
|
Big Data Research in Italy: A Perspective, file e0d6c928-5c4e-fcf8-e053-d805fe0aa794
|
142
|
|
null, file e0d6c92e-a739-fcf8-e053-d805fe0aa794
|
134
|
|
The layered structure of company share networks, file e0d6c92c-cb0c-fcf8-e053-d805fe0aa794
|
111
|
|
Introduction to special issue on computational methods for enforcing privacy and fairness in the knowledge society, file e0d6c92c-78f8-fcf8-e053-d805fe0aa794
|
110
|
|
Opening the black box: a primer for anti-discrimination, file e0d6c930-a6bd-fcf8-e053-d805fe0aa794
|
84
|
|
Meaningful Explanations of Black Box AI Decision Systems, file e0d6c92f-adb5-fcf8-e053-d805fe0aa794
|
74
|
|
Bias Discovery within Human Raters: A Case Study of the Jigsaw Dataset, file 0d5eab72-49a0-48da-8655-cada5b84769f
|
47
|
|
null, file e0d6c92c-5fa6-fcf8-e053-d805fe0aa794
|
47
|
|
Segregation discovery in a social network of companies, file e0d6c930-b94b-fcf8-e053-d805fe0aa794
|
44
|
|
A KDD process for discrimination discovery, file e0d6c930-bc51-fcf8-e053-d805fe0aa794
|
23
|
|
Bias in data-driven artificial intelligence systems—An introductory survey, file e0d6c92e-c7b4-fcf8-e053-d805fe0aa794
|
20
|
|
Causal inference for social discrimination reasoning, file e0d6c930-6214-fcf8-e053-d805fe0aa794
|
18
|
|
SCube: A tool for segregation discovery, file e0d6c92e-03bf-fcf8-e053-d805fe0aa794
|
13
|
|
Methods and tools for causal discovery and causal inference, file e0d6c932-211c-fcf8-e053-d805fe0aa794
|
13
|
|
Ensemble of Counterfactual Explainers, file e0d6c931-a100-fcf8-e053-d805fe0aa794
|
12
|
|
Introduction to the special issue on Artificial Intelligence for Society and Economy, file e0d6c92c-cb0b-fcf8-e053-d805fe0aa794
|
10
|
|
Sequential pattern mining for ICT risk assessment and prevention, file e0d6c92b-2a2d-fcf8-e053-d805fe0aa794
|
9
|
|
Introduction to The Special Section on Bias and Fairness in AI, file e0d6c931-aa62-fcf8-e053-d805fe0aa794
|
9
|
|
How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science, file d05975e9-a94c-410a-ad4b-a24614b02d27
|
5
|
|
Estimating the Total Volume of Queries to a Search Engine, file e0d6c931-6416-fcf8-e053-d805fe0aa794
|
4
|
|
Segregation discovery in a social network of companies, file cca6e71b-7e0d-48fb-a17d-0e3d6de74740
|
3
|
|
null, file e0d6c929-ba6f-fcf8-e053-d805fe0aa794
|
3
|
|
null, file e0d6c92c-ccf5-fcf8-e053-d805fe0aa794
|
3
|
|
Local Rule-Based Explanations of Black Box Decision Systems, file e0d6c92e-e63a-fcf8-e053-d805fe0aa794
|
3
|
|
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment, file e0d6c931-99fe-fcf8-e053-d805fe0aa794
|
3
|
|
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness, file 40d95d8b-e5c2-4a18-a151-9cff849d5c22
|
2
|
|
Data mining for intelligent web caching, file e0d6c926-1d27-fcf8-e053-d805fe0aa794
|
2
|
|
null, file e0d6c926-3f9e-fcf8-e053-d805fe0aa794
|
2
|
|
null, file e0d6c926-4a92-fcf8-e053-d805fe0aa794
|
2
|
|
null, file e0d6c92c-5ddc-fcf8-e053-d805fe0aa794
|
2
|
|
null, file e0d6c92c-5fa8-fcf8-e053-d805fe0aa794
|
2
|
|
Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars, file e0d6c92f-5b2b-fcf8-e053-d805fe0aa794
|
2
|
|
Sequential pattern mining for ICT risk assessment and management, file beb537a0-e964-485b-99ea-38ee07599bae
|
1
|
|
null, file e0d6c926-1a01-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c926-1b4b-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c926-42e0-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c92c-cb06-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c92d-8932-fcf8-e053-d805fe0aa794
|
1
|
|
On the Stability of Interpretable Models, file e0d6c930-66cf-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c930-9025-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c930-9843-fcf8-e053-d805fe0aa794
|
1
|
|
null, file e0d6c930-b954-fcf8-e053-d805fe0aa794
|
1
|
|
Trustworthy AI at KDD Lab, file e4d1d0fc-2149-4c01-b81e-2e806877e88b
|
1
|
| Totale |
2.622 |