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Continuous control tasks often involve high-dimensional, dynamic, and non-linear environments. State-of-the-art performance in these tasks is achieved through complex closed-box policies that are effective, but suffer from an inherent opacity. Interp
Externí odkaz:
http://arxiv.org/abs/2412.13053
Network pruning is a set of computational techniques that aim to reduce a given model's computational cost by removing a subset of its parameters while having minimal impact on performance. Throughout the last decade, the most widely used pruning par
Externí odkaz:
http://arxiv.org/abs/2411.07066
Hyperparameter optimization is a crucial problem in Evolutionary Computation. In fact, the values of the hyperparameters directly impact the trajectory taken by the optimization process, and their choice requires extensive reasoning by human operator
Externí odkaz:
http://arxiv.org/abs/2408.02451
The Influence Maximization (IM) problem seeks to discover the set of nodes in a graph that can spread the information propagation at most. This problem is known to be NP-hard, and it is usually studied by maximizing the influence (spread) and, option
Externí odkaz:
http://arxiv.org/abs/2403.18755
Reinforcement Learning (RL) bears the promise of being an enabling technology for many applications. However, since most of the literature in the field is currently focused on opaque models, the use of RL in high-stakes scenarios, where interpretabil
Externí odkaz:
http://arxiv.org/abs/2401.15480
Addressing the need for explainable Machine Learning has emerged as one of the most important research directions in modern Artificial Intelligence (AI). While the current dominant paradigm in the field is based on black-box models, typically in the
Externí odkaz:
http://arxiv.org/abs/2208.12758
Publikováno v:
Genetic and Evolutionary Computation Conference Companion (GECCO '22 Companion), July 9--13, 2022, Boston, MA, USA
Since the first wave of the COVID-19 pandemic, governments have applied restrictions in order to slow down its spreading. However, creating such policies is hard, especially because the government needs to trade-off the spreading of the pandemic with
Externí odkaz:
http://arxiv.org/abs/2204.04256
The importance of explainability in AI has become a pressing concern, for which several explainable AI (XAI) approaches have been recently proposed. However, most of the available XAI techniques are post-hoc methods, which however may be only partial
Externí odkaz:
http://arxiv.org/abs/2202.04943
In the last decade, deep neural networks have proven to be very powerful in computer vision tasks, starting a revolution in the computer vision and machine learning fields. However, deep neural networks, usually, are not robust to perturbations of th
Externí odkaz:
http://arxiv.org/abs/2104.15064
The evolution of symbolic communication is a longstanding open research question in biology. While some theories suggest that it originated from sub-symbolic communication (i.e., iconic or indexical), little experimental evidence exists on how organi
Externí odkaz:
http://arxiv.org/abs/2103.16882