Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Karimi, Amir Hossein"'
Autor:
Johnson, Samuel G. B., Karimi, Amir-Hossein, Bengio, Yoshua, Chater, Nick, Gerstenberg, Tobias, Larson, Kate, Levine, Sydney, Mitchell, Melanie, Rahwan, Iyad, Schölkopf, Bernhard, Grossmann, Igor
Recent advances in artificial intelligence (AI) have produced systems capable of increasingly sophisticated performance on cognitive tasks. However, AI systems still struggle in critical ways: unpredictable and novel environments (robustness), lack o
Externí odkaz:
http://arxiv.org/abs/2411.02478
Autor:
Machiraju, Gautam, Derry, Alexander, Desai, Arjun, Guha, Neel, Karimi, Amir-Hossein, Zou, James, Altman, Russ, Ré, Christopher, Mallick, Parag
Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical domains. Current methods for feature attribution, which rely on "explai
Externí odkaz:
http://arxiv.org/abs/2402.11729
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces
Autor:
Ehyaei, Ahmad-Reza, Mohammadi, Kiarash, Karimi, Amir-Hossein, Samadi, Samira, Farnadi, Golnoosh
As responsible AI gains importance in machine learning algorithms, properties such as fairness, adversarial robustness, and causality have received considerable attention in recent years. However, despite their individual significance, there remains
Externí odkaz:
http://arxiv.org/abs/2308.08938
Autor:
Akbari, Masoud, Karimi, Amir Hossein, Saeedi, Tayyebeh, Saeidi, Zeinab, Ghezelbash, Kiana, Shamsezat, Fatemeh, Akbari, Mohammad, Mohades, Ali
Natural Language Understanding (NLU) is important in today's technology as it enables machines to comprehend and process human language, leading to improved human-computer interactions and advancements in fields such as virtual assistants, chatbots,
Externí odkaz:
http://arxiv.org/abs/2303.00408
Algorithmic recourse aims to disclose the inner workings of the black-box decision process in situations where decisions have significant consequences, by providing recommendations to empower beneficiaries to achieve a more favorable outcome. To ensu
Externí odkaz:
http://arxiv.org/abs/2302.03465
Being able to provide explanations for a model's decision has become a central requirement for the development, deployment, and adoption of machine learning models. However, we are yet to understand what explanation methods can and cannot do. How do
Externí odkaz:
http://arxiv.org/abs/2212.06925
Publikováno v:
In Progress in Organic Coatings November 2024 196
Algorithmic recourse seeks to provide actionable recommendations for individuals to overcome unfavorable classification outcomes from automated decision-making systems. Recourse recommendations should ideally be robust to reasonably small uncertainty
Externí odkaz:
http://arxiv.org/abs/2112.11313
Autor:
Dawson, Alice, Karimi, Amir Hossein, Shaikh, Mushfiq H., Gazala, Walid, Zeng, Peter Y.F., Ryan, Sarah E.B., Pan, Harrison, Khan, Halema, Cecchini, Matthew, Mendez, Adrian, Palma, David A., Mymryk, Joe S., Barrett, John W., Nichols, Anthony C.
Publikováno v:
In Oral Oncology December 2024 159
Autor:
Choopani, Leila, Aliabadi, Hooman Aghamirza Moghim, Ganjali, Fatemeh, Kashtiaray, Amir, Eivazzadeh-Keihan, Reza, Maleki, Ali, Salimibani, Milad, Karimi, Amir Hossein, Salehpour, Nabi, Mahdavi, Mohammad
Publikováno v:
In Carbohydrate Polymer Technologies and Applications June 2024 7