Zobrazeno 1 - 10
of 401
pro vyhledávání: '"Carey Ryan"'
Publikováno v:
Frontiers in Psychology, Vol 14 (2023)
The objective of this research was to examine gender differences in entrepreneurial venture interests drawing on goal congruity theory, which posits that people adopt gender-stereotypic goal orientations in response to social pressures to conform to
Externí odkaz:
https://doaj.org/article/6c9b972e02534aafbd89d347d3d4ab73
In a decision problem, observations are said to be material if they must be taken into account to perform optimally. Decision problems have an underlying (graphical) causal structure, which may sometimes be used to evaluate certain observations as im
Externí odkaz:
http://arxiv.org/abs/2407.09883
Autor:
Luo, Zhishang, Hy, Truong Son, Tabaghi, Puoya, Koh, Donghyeon, Defferrard, Michael, Rezaei, Elahe, Carey, Ryan, Davis, Rhett, Jain, Rajeev, Wang, Yusu
The run-time for optimization tools used in chip design has grown with the complexity of designs to the point where it can take several days to go through one design cycle which has become a bottleneck. Designers want fast tools that can quickly give
Externí odkaz:
http://arxiv.org/abs/2404.00477
While graph neural networks (GNNs) have gained popularity for learning circuit representations in various electronic design automation (EDA) tasks, they face challenges in scalability when applied to large graphs and exhibit limited generalizability
Externí odkaz:
http://arxiv.org/abs/2403.01317
Autor:
Carey, Ryan, Everitt, Tom
How can humans stay in control of advanced artificial intelligence systems? One proposal is corrigibility, which requires the agent to follow the instructions of a human overseer, without inappropriately influencing them. In this paper, we formally d
Externí odkaz:
http://arxiv.org/abs/2305.19861
Autor:
Hammond, Lewis, Fox, James, Everitt, Tom, Carey, Ryan, Abate, Alessandro, Wooldridge, Michael
Causal reasoning and game-theoretic reasoning are fundamental topics in artificial intelligence, among many other disciplines: this paper is concerned with their intersection. Despite their importance, a formal framework that supports both these form
Externí odkaz:
http://arxiv.org/abs/2301.02324
We present a general framework for training safe agents whose naive incentives are unsafe. As an example, manipulative or deceptive behaviour can improve rewards but should be avoided. Most approaches fail here: agents maximize expected return by any
Externí odkaz:
http://arxiv.org/abs/2204.10018
Autor:
Chowdhury, Animesh Basak, Tan, Benjamin, Carey, Ryan, Jain, Tushit, Karri, Ramesh, Garg, Siddharth
Generating sub-optimal synthesis transformation sequences ("synthesis recipe") is an important problem in logic synthesis. Manually crafted synthesis recipes have poor quality. State-of-the art machine learning (ML) works to generate synthesis recipe
Externí odkaz:
http://arxiv.org/abs/2204.02368
Influence diagrams have recently been used to analyse the safety and fairness properties of AI systems. A key building block for this analysis is a graphical criterion for value of information (VoI). This paper establishes the first complete graphica
Externí odkaz:
http://arxiv.org/abs/2202.11629
In addition to reproducing discriminatory relationships in the training data, machine learning systems can also introduce or amplify discriminatory effects. We refer to this as introduced unfairness, and investigate the conditions under which it may
Externí odkaz:
http://arxiv.org/abs/2202.10816