Zobrazeno 1 - 10
of 3 516
pro vyhledávání: '"Dickerson, John"'
Clustering is a fundamental problem in machine learning and operations research. Therefore, given the fact that fairness considerations have become of paramount importance in algorithm design, fairness in clustering has received significant attention
Externí odkaz:
http://arxiv.org/abs/2406.15960
In barter exchanges agents enter seeking to swap their items for other items on their wishlist. We consider a centralized barter exchange with a set of agents and items where each item has a positive value. The goal is to compute a (re)allocation of
Externí odkaz:
http://arxiv.org/abs/2406.13983
We study the canonical fair clustering problem where each cluster is constrained to have close to population-level representation of each group. Despite significant attention, the salient issue of having incomplete knowledge about the group membershi
Externí odkaz:
http://arxiv.org/abs/2406.00599
Responsible artificial intelligence (RAI) is increasingly recognized as a critical concern. However, the level of corporate RAI prioritization has not kept pace. In this work, we conduct 16 semi-structured interviews with practitioners to investigate
Externí odkaz:
http://arxiv.org/abs/2405.03855
Large language models (LLMs) are increasing in capability and popularity, propelling their application in new domains -- including as replacements for human participants in computational social science, user testing, annotation tasks, and more. Tradi
Externí odkaz:
http://arxiv.org/abs/2402.01908
Autor:
Verma, Sahil, Bhatt, Gantavya, Schwarzschild, Avi, Singhal, Soumye, Das, Arnav Mohanty, Shah, Chirag, Dickerson, John P, Bilmes, Jeff
Despite the advanced capabilities of contemporary machine learning (ML) models, they remain vulnerable to adversarial and backdoor attacks. This vulnerability is particularly concerning in real-world deployments, where compromised models may exhibit
Externí odkaz:
http://arxiv.org/abs/2311.14948
Research in fair machine learning, and particularly clustering, has been crucial in recent years given the many ethical controversies that modern intelligent systems have posed. Ahmadian et al. [2020] established the study of fairness in \textit{hier
Externí odkaz:
http://arxiv.org/abs/2311.12501
Most reinforcement learning methods rely heavily on dense, well-normalized environment rewards. DreamerV3 recently introduced a model-based method with a number of tricks that mitigate these limitations, achieving state-of-the-art on a wide range of
Externí odkaz:
http://arxiv.org/abs/2310.17805
Recommender systems play an essential role in the choices people make in domains such as entertainment, shopping, food, news, employment, and education. The machine learning models underlying these recommender systems are often enormously large and b
Externí odkaz:
http://arxiv.org/abs/2308.14916