615 research outputs found
EMaP: Explainable AI with Manifold-based Perturbations
In the last few years, many explanation methods based on the perturbations of
input data have been introduced to improve our understanding of decisions made
by black-box models. The goal of this work is to introduce a novel perturbation
scheme so that more faithful and robust explanations can be obtained. Our study
focuses on the impact of perturbing directions on the data topology. We show
that perturbing along the orthogonal directions of the input manifold better
preserves the data topology, both in the worst-case analysis of the discrete
Gromov-Hausdorff distance and in the average-case analysis via persistent
homology. From those results, we introduce EMaP algorithm, realizing the
orthogonal perturbation scheme. Our experiments show that EMaP not only
improves the explainers' performance but also helps them overcome a
recently-developed attack against perturbation-based methods.Comment: 29 page
FedMEKT: Distillation-based Embedding Knowledge Transfer for Multimodal Federated Learning
Federated learning (FL) enables a decentralized machine learning paradigm for
multiple clients to collaboratively train a generalized global model without
sharing their private data. Most existing works simply propose typical FL
systems for single-modal data, thus limiting its potential on exploiting
valuable multimodal data for future personalized applications. Furthermore, the
majority of FL approaches still rely on the labeled data at the client side,
which is limited in real-world applications due to the inability of
self-annotation from users. In light of these limitations, we propose a novel
multimodal FL framework that employs a semi-supervised learning approach to
leverage the representations from different modalities. Bringing this concept
into a system, we develop a distillation-based multimodal embedding knowledge
transfer mechanism, namely FedMEKT, which allows the server and clients to
exchange the joint knowledge of their learning models extracted from a small
multimodal proxy dataset. Our FedMEKT iteratively updates the generalized
global encoders with the joint embedding knowledge from the participating
clients. Thereby, to address the modality discrepancy and labeled data
constraint in existing FL systems, our proposed FedMEKT comprises local
multimodal autoencoder learning, generalized multimodal autoencoder
construction, and generalized classifier learning. Through extensive
experiments on three multimodal human activity recognition datasets, we
demonstrate that FedMEKT achieves superior global encoder performance on linear
evaluation and guarantees user privacy for personal data and model parameters
while demanding less communication cost than other baselines
HierarchyNet : learning to summarize source code with heterogeneous representations
Code representation is important to machine learning models in the code-related applications. Existing code summarization approaches primarily leverage Abstract Syntax Trees (ASTs) and sequential information from source code to generate code summaries while often overlooking the critical consideration of the interplay of dependencies among code elements and code hierarchy. However, effective summarization necessitates a holistic analysis of code snippets from three distinct aspects: lexical, syntactic, and semantic information. In this paper, we propose a novel code summarization approach utilizing Heterogeneous Code Representations (HCRs) and our specially designed HierarchyNet. HCRs adeptly capture essential code features at lexical, syntactic, and semantic levels within a hierarchical structure. HierarchyNet processes each layer of the HCR separately, employing a Heterogeneous Graph Transformer, a Tree-based CNN, and a Transformer Encoder. In addition, HierarchyNet demonstrates superior performance compared to fine-tuned pre-trained models, including CodeT5, and CodeBERT, as well as large language models that employ zero/few-shot settings, such as CodeLlama, StarCoder, and CodeGen. Implementation details can be found at https://github.com/FSoft-AI4Code/HierarchyNet
Security and reliability analysis of a two-way half-duplex wireless relaying network using partial relay selection and hybrid TPSR energy harvesting at relay nodes
In recent years, physical layer security has been considered as an effective method to enhance the information security beside the cryptographic techniques that are used in upper layers. In this paper, we provide the security analysis for a two-way relay network, where the two sources can only communicate through the intermediate relay nodes. In particular, we consider the scenario that there is an eavesdropper in the vicinity of one source node. Both reliability and security aspects are taken into consideration in our work. To enhance the reliability of communication, the intermediate relays are supplied with the energy harvested from the sources radio frequency (RF) signals using hybrid time-switching and power splitting (TPSR) protocol. Also, we apply the relay selection technique to select the best relay for the information exchange between two sources. Regarding security, the secrecy of information is improved with the help of friendly jammers nearby the eavesdropper. We provide the in-dept reliability and security analysis in terms of the closed-form expressions of the outage probability (OP) at the source nodes, the intercept probability (IP) at the eavesdropper, the secrecy outage probability (SOP), and the average secrecy capacity (ASC) of the system. Finally, the Monte Carlo simulations are also conducted to verify the correctness of our analysis and the effectiveness of the proposed scheme. Numerical results confirms that with the appropriate and feasible choices of involved parameters, both outage OP and IP can be kept at small values to guarantee the reliable and secure communication of the system.Web of Science818718118716
Solvent-Induced Reversal of Activities between Two Closely Related Heterogeneous Catalysts in the Aldol Reaction
The relative rates of the aldol reaction catalyzed by supported primary and secondary amines can be inverted by 2 orders of magnitude, depending on the use of hexane or water as a solvent. Our analyses suggest that this dramatic shift in the catalytic behavior of the supported amines does not involve differences in reaction mechanism, but is caused by activation of imine to enamine equilibria and stabilization of iminium species. The effects of solvent polarity and acidity were found to be important to the performance of the catalytic reaction. This study highlights the critical role of solvent in multicomponent heterogeneous catalytic processes
Gravitational Waves From Known Pulsars: Results From The Initial Detector Era
We present the results of searches for gravitational waves from a large selection of pulsars using data from the most recent science runs (S6, VSR2 and VSR4) of the initial generation of interferometric gravitational wave detectors LIGO (Laser Interferometric Gravitational-wave Observatory) and Virgo. We do not see evidence for gravitational wave emission from any of the targeted sources but produce upper limits on the emission amplitude. We highlight the results from seven young pulsars with large spin-down luminosities. We reach within a factor of five of the canonical spin-down limit for all seven of these, whilst for the Crab and Vela pulsars we further surpass their spin-down limits. We present new or updated limits for 172 other pulsars (including both young and millisecond pulsars). Now that the detectors are undergoing major upgrades, and, for completeness, we bring together all of the most up-to-date results from all pulsars searched for during the operations of the first-generation LIGO, Virgo and GEO600 detectors. This gives a total of 195 pulsars including the most recent results described in this paper.United States National Science FoundationScience and Technology Facilities Council of the United KingdomMax-Planck-SocietyState of Niedersachsen/GermanyAustralian Research CouncilInternational Science Linkages program of the Commonwealth of AustraliaCouncil of Scientific and Industrial Research of IndiaIstituto Nazionale di Fisica Nucleare of ItalySpanish Ministerio de Economia y CompetitividadConselleria d'Economia Hisenda i Innovacio of the Govern de les Illes BalearsNetherlands Organisation for Scientific ResearchPolish Ministry of Science and Higher EducationFOCUS Programme of Foundation for Polish ScienceRoyal SocietyScottish Funding CouncilScottish Universities Physics AllianceNational Aeronautics and Space AdministrationOTKA of HungaryLyon Institute of Origins (LIO)National Research Foundation of KoreaIndustry CanadaProvince of Ontario through the Ministry of Economic Development and InnovationNational Science and Engineering Research Council CanadaCarnegie TrustLeverhulme TrustDavid and Lucile Packard FoundationResearch CorporationAlfred P. Sloan FoundationAstronom
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