Zobrazeno 1 - 10
of 21 057
pro vyhledávání: '"A. Minas"'
This research explores the interdisciplinary interaction between psychoanalysis and computer science, suggesting a mutually beneficial exchange. Indeed, psychoanalytic concepts can enrich technological applications involving unconscious, elusive aspe
Externí odkaz:
http://arxiv.org/abs/2410.22895
The UNESCO (2022) points out that the gap between the existing awareness of a person or a community, and the actual habits of everyday life, is attributed to: low levels of understanding the environmental issues at stake; low levels of knowledge rega
Externí odkaz:
http://arxiv.org/abs/2410.10586
This study aims to develop models that generate corpus informed clarifying questions for web search, in a way that ensures the questions align with the available information in the retrieval corpus. We demonstrate the effectiveness of Retrieval Augme
Externí odkaz:
http://arxiv.org/abs/2409.18575
Autor:
Cutler, Elizabeth, Xing, Yuning, Cui, Tony, Zhou, Brendan, van Rijnsoever, Koen, Hart, Ben, Valencia, David, Ong, Lee Violet C., Gee, Trevor, Liarokapis, Minas, Williams, Henry
Publikováno v:
Australasian conference on robotics and automation (ACRA 2023)
Reinforcement Learning (RL) training is predominantly conducted in cost-effective and controlled simulation environments. However, the transfer of these trained models to real-world tasks often presents unavoidable challenges. This research explores
Externí odkaz:
http://arxiv.org/abs/2408.14747
Autor:
Valencia, David, Williams, Henry, Xing, Yuning, Gee, Trevor, Liarokapis, Minas, MacDonald, Bruce A.
Reinforcement Learning (RL) has been widely used to solve tasks where the environment consistently provides a dense reward value. However, in real-world scenarios, rewards can often be poorly defined or sparse. Auxiliary signals are indispensable for
Externí odkaz:
http://arxiv.org/abs/2407.21338
Autor:
Karamanis, Minas, Seljak, Uroš
Sequential Monte Carlo (SMC) methods are powerful tools for Bayesian inference but suffer from requiring many particles for accurate estimates, leading to high computational costs. We introduce persistent sampling (PS), an extension of SMC that mitig
Externí odkaz:
http://arxiv.org/abs/2407.20722
Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of
Externí odkaz:
http://arxiv.org/abs/2407.07781
CTD4 -- A Deep Continuous Distributional Actor-Critic Agent with a Kalman Fusion of Multiple Critics
Categorical Distributional Reinforcement Learning (CDRL) has demonstrated superior sample efficiency in learning complex tasks compared to conventional Reinforcement Learning (RL) approaches. However, the practical application of CDRL is encumbered b
Externí odkaz:
http://arxiv.org/abs/2405.02576
We show that the maximal shifts in the minimal free resolution of the quotients of a polynomial ring by a monomial ideal are subadditive as a function of the homological degree. This answers a question that has received some attention in recent years
Externí odkaz:
http://arxiv.org/abs/2404.16643
Engelfriet and Vereijken have shown that linear graph grammars based on hyperedge replacement generate graph languages that can be considered as interpretations of regular string languages over typed symbols. In this paper we show that finite automat
Externí odkaz:
http://arxiv.org/abs/2404.15052