Heavy-tailed distributions in haptic perception of wielded rods.
Sign Up to like & getrecommendations! Published in 2021 at "Experimental brain research"
DOI: 10.1007/s00221-021-06131-7
Abstract: Humans identify properties (e.g., the length or weight) of objects through touch using somatosensory perceptions in the limbs. Humans identify these properties by manipulating an object to access its inertial qualities. However, there is little… read more here.
Keywords: haptic perception; angular acceleration; heavy tailed; tailed distributions ... See more keywords
Generative models of simultaneously heavy-tailed distributions of interevent times on nodes and edges.
Sign Up to like & getrecommendations! Published in 2020 at "Physical Review E"
DOI: 10.1103/physreve.102.052303
Abstract: Intervals between discrete events representing human activities, as well as other types of events, often obey heavy-tailed distributions, and their impacts on collective dynamics on networks such as contagion processes have been intensively studied. The… read more here.
Keywords: heavy tailed; nodes edges; tailed distributions; interevent times ... See more keywords
Distinguishing subsampled power laws from other heavy-tailed distributions.
Sign Up to like & getrecommendations! Published in 2024 at "Physical review. E"
DOI: 10.1103/physreve.109.054308
Abstract: Distinguishing power-law distributions from other heavy-tailed distributions is challenging, and this task is often further complicated by subsampling effects. In this work, we evaluate the performance of two commonly used methods for detecting power-law distributions-the… read more here.
Keywords: method; power law; heavy tailed; tailed distributions ... See more keywords
Exploring Amplified Heterogeneity Arising From Heavy-Tailed Distributions in Federated Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Mobile Computing"
DOI: 10.1109/tmc.2024.3398052
Abstract: Federated Learning (FL) has emerged as a privacy-preserving paradigm enabling collaborative model training among distributed clients. However, current FL methods operate under the closed-world assumption, i.e., all local training data originates from a global labeled… read more here.
Keywords: exploring amplified; heavy tailed; federated learning; aggregation ... See more keywords