Byzantine-robust federated learning via credibility assessment on non-IID data.

Federated learning is a novel framework that enables resource-constrained edge devices to jointly learn a model, which solves the problem of data protection and data islands. However, standard federated learning is vulnerable to Byzantine attacks, which will cause the global model to be manipulated by the attacker or fail to converge. On non-iid data, the current methods are not effective in defensing against Byzantine attacks.

Denoising Protein-Protein interaction network via variational graph auto-encoder for protein complex detection.

Identifying protein complexes is an important issue in computational biology, as it benefits the understanding of cellular functions and the design of drugs. In the past decades, many computational methods have been proposed by mining dense subgraphs in Protein-Protein Interaction Networks (PINs). However, the high rate of false positive/negative interactions in PINs prevents accurately detecting complexes directly from the raw PINs.

P300 as an index of transition to psychosis and of remission: Data from a clinical high risk for psychosis study and review of literature.

Auditory P300 oddball and novel components index working memory operations and salience processing, respectively, and are regarded as biomarkers of neurocognitive changes in both chronic and first-episode schizophrenia. Much less is known about whether P300 abnormalities exist in individuals at clinical high risk for psychosis (CHR) and if they are predictors of both transition to psychosis and remission from symptoms. One hundred and four CHR and 69 healthy control individuals (HC) completed P300 oddball paradigm, and 131 CHR and 69 HC subjects completed P300 novel paradigm.

Link Prediction based on Quantum-Inspired Ant Colony Optimization.

Incomplete or partial observations of network structures pose a serious challenge to theoretical and engineering studies of real networks. To remedy the missing links in real datasets, topology-based link prediction is introduced into the studies of various networks. Due to the complexity of network structures, the accuracy and robustness of most link prediction algorithms are not satisfying enough.

Precise theta burst transcranial magnetic stimulation selectively reduced duration-related mismatch negativity.

Background: Mismatch negativity (MMN) is a typical event-related potential component reflecting pre-attentive processing. MMN impairment, especially reduced duration-related MMN (dMMN), has been suggested as a potential predictive biomarker for the onset of schizophrenia.

Objective: This study attempts to manipulate specific MMN activities using advanced neuroimaging-guided intermittent theta-burst stimulations (iTBS), which will be helpful to uncover the sources of MMN generation and contribute to the development of new clinical treatments.

Impact of directionality and correlation on contagion.

The threshold model has been widely adopted for modelling contagion processes on social networks, where individuals are assumed to be in one of two states: inactive or active. This paper studies the model on directed networks where nodal inand out-degrees may be correlated. To understand how directionality and correlation affect the breakdown of the system, a theoretical framework based on generating function technology is developed.

Divide-and-conquer Tournament on Social Networks.

In social gaming networks, previous studies extensively investigated the influence of a variety of strategies on reciprocal behaviors in the prisoner's dilemma game. The studied frameworks range from the case that an individual uniformly cooperates or defects with all social contacts, to the recently reported divide-and-conquer games, where an individual can choose a particular move to play with each neighbor. In this paper, we investigate a divide-and-conquer tournament among 14 well-known strategies on social gaming networks.

Heuristic Strategies for Persuader Selection in Contagions on Complex Networks.

Individual decision to accept a new idea or product is often driven by both self-adoption and others' persuasion, which has been simulated using a double threshold model [Huang et al., Scientific Reports 6, 23766 (2016)]. We extend the study to consider the case with limited persuasion.