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PEN4Rec: Preference Evolution Networks for Session-based Recommendation
[article]
2021
arXiv
pre-print
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Session-based recommendation aims to predict user the next action based on historical behaviors in an anonymous session. For better recommendations, it is vital to capture user preferences as well as their dynamics. Besides, user preferences evolve over time dynamically and each preference has its own evolving track. However, most previous works neglect the evolving trend of preferences and can be easily disturbed by the effect of preference drifting. In this paper, we propose a novel
arXiv:2106.09306v1
fatcat:nroiymtytbgnhclaxzauvniwcu
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... Evolution Networks for session-based Recommendation (PEN4Rec) to model preference evolving process by a two-stage retrieval from historical contexts. Specifically, the first-stage process integrates relevant behaviors according to recent items. Then, the second-stage process models the preference evolving trajectory over time dynamically and infer rich preferences. The process can strengthen the effect of relevant sequential behaviors during the preference evolution and weaken the disturbance from preference drifting. Extensive experiments on three public datasets demonstrate the effectiveness and superiority of the proposed model.
DePET: A Decentralized Privacy-Preserving Energy Trading Scheme for Vehicular Energy Network via Blockchain and K -anonymity
2020
IEEE Access
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Improving Adversarial Robustness via Attention and Adversarial Logit Pairing
[article]
2021
arXiv
pre-print
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Though deep neural networks have achieved the state of the art performance in visual classification, recent studies have shown that they are all vulnerable to the attack of adversarial examples. In this paper, we develop improved techniques for defending against adversarial examples. First, we propose an enhanced defense technique denoted Attention and Adversarial Logit Pairing(AT+ALP), which encourages both attention map and logit for the pairs of examples to be similar. When being applied to
arXiv:1908.11435v2
fatcat:hemenmkb6jhcjjg5f5zuywlb64
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... lean examples and their adversarial counterparts, AT+ALP improves accuracy on adversarial examples over adversarial training. We show that AT+ALP can effectively increase the average activations of adversarial examples in the key area and demonstrate that it focuses on discriminate features to improve the robustness of the model. Finally, we conduct extensive experiments using a wide range of datasets and the experiment results show that our AT+ALP achieves the state of the art defense performance. For example, on 17 Flower Category Database, under strong 200-iteration PGD gray-box and black-box attacks where prior art has 34 39 work is evaluated under highly challenging PGD attack: the maximum perturbation ϵ∈{0.25,0.5} i.e. L_∞∈{0.25,0.5} with 10 to 200 attack iterations. To the best of our knowledge, such a strong attack has not been previously explored on a wide range of datasets.
Identification of Bufavirus-1 and Bufavirus-3 in Feces of Patients with Acute Diarrhea, China
2015
Scientific Reports
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Bufavirus (BuV) is a newly discovered human parvovirus that has been detected in some countries. The current study was designed to understand the epidemic of BuV in China. Totally 1877 fecal specimens were collected from pediatric and adult patients with acute diarrhea in two large hospitals from 2010 to 2014. BuV was detected in 0.5% (9/1877) of the fecal samples by PCR and subsequent sequencing. The positive patients had a wide age range from 1 month through 60 years (median 24 years old) and
doi:10.1038/srep13272
pmid:26286376
pmcid:PMC4541159
fatcat:eq45sdqv55b6zptkxr4iaazkom
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... 6 were male. A geographic specific pattern was obvious, with significantly higher frequency of BuV presented in Northern than in Southern China. Four BuV-1 and five BuV-3 were determined. Mixed-infections of BuV with sapovirus and novavirus were found in 2 cases, respectively. A temporal clustering was identified, with most positive detection focused in the cold weather. These findings have expanded the current knowledge on the geographic boundaries of BuV circulation.
Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detection
[article]
2021
arXiv
pre-print
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Wei et al. (2019) jointly modeled the structural property by GCN and the temporal evolution by RNN.
Figure 2 : 2 The architecture of the proposed rumor detection model EBGCN. ...
arXiv:2107.11934v1
fatcat:bosu37bur5dtrctae5y4sa233m
Estimation in Functional Regression for General Exponential Families
[article]
2011
arXiv
pre-print
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In a companion study to our paper, Dou (2010, Chapter 5) considers optimal prediction in functional generalized linear regressions with an application to the economic problem of predicting occurrence ...
arXiv:1108.3552v1
fatcat:dl36z3g465e5pghzklw5fltdue
Determination of Instars of Bactrocera dorsalis (Diptera: Tephritidae)
2017
Florida Entomologist
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Vibration-Induced-Emission (VIE) for imaging amyloid β fibrils
2017
Faraday discussions
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This paper discusses the use of N,N′-disubstituted-dihydrodibenzo[a,c]phenazines with typical Vibration-Induced-Emission (VIE) properties for imaging amyloid β (Aβ) fibrils, which are a signature of neurological disorders such as Alzheimer's disease. A water-soluble VIEgen with a red fluorescence emission shows a pronounced, blue-shifted emission with Aβ peptide monomers and fibrils. The enhancement in blue fluorescence can be ascribed to the restriction of the molecular vibration by
doi:10.1039/c6fd00156d
pmid:27898114
fatcat:pxcylzz2treh7ia3zkmdrngvw4
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... binding to Aβ. We determine an increasing blue-to-red emission ratio of the VIEgen with both the concentration and fibrogenesis time of Aβ, thereby enabling a ratiometric detection of Aβ in its different morphological forms. Importantly, the VIEgen was proven to be suitable for the fluorescence imaging of small Aβ plaques in the hippocampus of a transgenic mouse brain (five months old), with the blue and red emissions well overlapped on the Aβ. This research offers a new rationale to design molecular VIE probes for biological applications.
Mammalian PIK3C3/VPS34
2012
Autophagy
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Adversarial Attention-Based Variational Graph Autoencoder
2020
IEEE Access
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Inductive Matrix Completion Using Graph Autoencoder
[article]
2021
arXiv
pre-print
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Recently, the graph neural network (GNN) has shown great power in matrix completion by formulating a rating matrix as a bipartite graph and then predicting the link between the corresponding user and item nodes. The majority of GNN-based matrix completion methods are based on Graph Autoencoder (GAE), which considers the one-hot index as input, maps a user (or item) index to a learnable embedding, applies a GNN to learn the node-specific representations based on these learnable embeddings and
arXiv:2108.11124v1
fatcat:pzpgh7u3wza6dhezl5b2vrvkhi
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... ally aggregates the representations of the target users and its corresponding item nodes to predict missing links. However, without node content (i.e., side information) for training, the user (or item) specific representation can not be learned in the inductive setting, that is, a model trained on one group of users (or items) cannot adapt to new users (or items). To this end, we propose an inductive matrix completion method using GAE (IMC-GAE), which utilizes the GAE to learn both the user-specific (or item-specific) representation for personalized recommendation and local graph patterns for inductive matrix completion. Specifically, we design two informative node features and employ a layer-wise node dropout scheme in GAE to learn local graph patterns which can be generalized to unseen data. The main contribution of our paper is the capability to efficiently learn local graph patterns in GAE, with good scalability and superior expressiveness compared to previous GNN-based matrix completion methods. Furthermore, extensive experiments demonstrate that our model achieves state-of-the-art performance on several matrix completion benchmarks. Our official code is publicly available.
Recent Progress in Graphite Intercalation Compounds for Rechargeable Metal (Li, Na, K, Al)-Ion Batteries
2017
Advanced Science
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Anticancer Action and Pharmacokinetics of Sesquiterpene Lactone Extracts of Yacon Leaves
2017
International Journal of Pharmacology
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Module for arbitrary controlled rotation in gate-based quantum algorithms
[article]
2021
arXiv
pre-print
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To assess whether a gate-based quantum algorithm can be executed successfully on a noisy intermediate-scale quantum (NISQ) device, both complexity and actual value of quantum resources should be considered carefully. Based on quantum phase estimation, we implemente arbitrary controlled rotation of quantum algorithms with a proposed modular method. The proposed method is not limited to be used as a submodule of the HHL algorithm and can be applied to more general quantum machine learning
arXiv:2107.08168v1
fatcat:6f4epmdun5gutbjp6ywpmidfqm
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... ms. Compared with the polynomial-fitting function method, our method only requires the least ancillas and the least quantum gates to maintain the high fidelity of quantum algorithms. The method theoretically will not influence the acceleration of original algorithms. Numerical simulations illustrate the effectiveness of the proposed method. Furthermore, if the corresponding diagonal unitary matrix can be effectively decomposed, the method is also polynomial in time cost.
Pre-Stimulus Alpha-Band Phase Gates Afferent Visual Cortex Responses
[article]
2021
bioRxiv
pre-print
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The neurogenesis of alpha-band (8-13 Hz) activity has been characterized across many different animal experiments. However, the functional role that alpha oscillations play in perception and behavior has largely been attributed to two contrasting hypotheses, with human evidence in favor of either (or both or neither) remaining sparse. On the one hand, alpha generators have been observed in relay sectors of the visual thalamus and are postulated to phasically inhibit afferent visual input in a
doi:10.1101/2021.04.06.438680
fatcat:wi7lbeqsnrafzj4si2esb4ptxe
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... edforward manner 1-4. On the other hand, evidence also suggests that the direction of influence of alpha activity propagates backwards along the visual hierarchy, reflecting a feedback influence upon the visual cortex 5-9. The primary source of human evidence regarding the role of alpha phase in visual processing has been on perceptual reports 10-16, which could be modulated either by feedforward or feedback alpha activity. Thus, although these two hypotheses are not mutually exclusive, human evidence clearly supporting either one is lacking. Here, we present human subjects with large, high-contrast visual stimuli that elicit robust C1 event-related potentials (ERP), which peak between 70-80 milliseconds post-stimulus and are thought to reflect afferent primary visual cortex (V1) input 17-20. We find that the phase of ongoing alpha oscillations modulates the global field power (GFP) of the EEG during this first volley of stimulus processing (the C1 time-window). On the standard assumption 21-23 that this early activity reflects postsynaptic potentials being relayed to visual cortex from the thalamus, our results suggest that alpha phase gates visual responses during the first feed-forward sweep of processing.
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