The automatic generation of music comments is of great significance for increasing the popularity of music and the music platform’s activity. In human music comments, there exists high distinction and diverse perspec...
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Evolution is the driving force behind the evolution of biological intelligence. Learning is the driving force behind human civilization. The combination of evolution and learning can form an entire natural world. Now,...
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Evolution is the driving force behind the evolution of biological intelligence. Learning is the driving force behind human civilization. The combination of evolution and learning can form an entire natural world. Now, reinforcement learning has shown significant effects in many places. However, Currently, researchers in the field of optimization algorithms mainly focus on evolution *** there is very little research on learning. Inspired by these ideas,this paper proposes a new particle swarm optimization algorithm Reinforcement learning based Ensemble particle swarm optimizer(RLEPSO) that combines reinforcement learning. The algorithm uses reinforcement learning for pre-training in the design phase to automatically find a more effective combination of parameters for the algorithm to run better and Complete optimization tasks faster. Besides, this algorithm integrates two robust particle swarm variants. And it sets the weight parameters for different algorithms to better adapt to the solution requirements of a variety of different optimization problems, which significantly improves the robustness of the algorithm. RLEPSO makes a certain number of sub-swarms to increase the probability of finding the global optimum and increasing the diversity of particle swarms. This proposed RLEPSO is evaluated on an optimization test functions benchmark set(CEC2013) with 28 functions and compared with other eight particle swarm optimization variants, including three state-of-theart optimization algorithms. The results show that RLEPSO has better performance and outperforms all compared algorithms.
Conventional federated learning (FL) coordinated by a central server focuses on training a global model and protecting the privacy of clients' training data by storing it locally. However, the statistical heteroge...
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The widespread adoption of emerging technologies, such as interconnected sensors and advanced automation systems, has led to rapid advancements in smart industrial environments. While industrial cyber-physical systems...
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This paper delves into an integrated sensing and communication (ISAC) system bolstered by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Within this system, a base station ...
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Single sign-on (SSO) services are widely deployed on the Internet as the identity management and authentication infrastructure. In an SSO system, after authenticated by the identity providers (IdPs), a user is allowed...
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ISBN:
(纸本)9781665424509
Single sign-on (SSO) services are widely deployed on the Internet as the identity management and authentication infrastructure. In an SSO system, after authenticated by the identity providers (IdPs), a user is allowed to log into relying parties (RPs) by submitting an identity proof. However, SSO introduces the potential leakage of user privacy, which is indicated by NIST. That is (a) a curious IdP could track a user's all visits to any RPs and (b) collusive RPs could link the user's identities across different RPs, to learn the user's activity profile. NIST suggests that the Pairwise Pseudonymous Identifier (PPID) should be adopted to prevent collusive RPs from linking the same user, as PPID mechanism enables an IdP to provide a user with multiple individual IDs for different RPs. However, PPID mechanism cannot protect users from IdP's tracking, as it still exposes RP identity to IdP. In this paper, we propose an SSO system, named UP-SSO, providing the enhanced PPID mechanism to protect a user's profile of RP visits from both the curious IdP and the collusive RPs by integrating PPID and SGX. It separates an IdP service into two parts, the server-side service and user-side service. The generation of PPID is shifted from IdP server to user client, so that IdP server no longer needs to learn RP ID. The integrity of user client can be verified by IdP through remote attestation. The detailed design of UP-SSO is described in this paper, and the systemic analysis is provided to guarantee its security. We implemented the prototype system of UP-SSO, and the evaluation of the prototype system shows the overhead is modest.
In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo. However, most of these methods lose information during the iterative process, making it...
In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo. However, most of these methods lose information during the iterative process, making it difficult to generate more detailed difference maps that take full advantage of high-frequency information. We propose the Decouple module to alleviate the problem of data coupling and allow features containing subtle details to transfer across the iterations which proves to alleviate the problem significantly in the ablations. To further capture high-frequency details, we propose a Normalization Refinement module that unifies the disparities as a proportion of the disparities over the width of the image, which address the problem of module failure in cross-domain scenarios. Further, with the above improvements, the ResNet-like feature extractor that has not been changed for years becomes a bottleneck. Towards this end, we proposed a multi-scale and multi-stage feature extractor that introduces the channel-wise self-attention mechanism which greatly addresses this bottleneck. Our method (DLNR) ranks 1st on the Middlebury leaderboard, significantly outperforming the next best method by 13.04%. Our method also achieves SOTA performance on the KITTI-2015 benchmark for D1-fg. Code and demos are available at: https://***/David-Zhao-1997/High-frequency-Stereo-Matching-network.
Modeling stochastic phenomena in continuous time is an essential yet challenging problem. Analytic solutions are often unavailable, and numerical methods can be prohibitively time-consuming and computationally expensi...
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Multimodal fake news is more deceptive than unimodal content and often has adverse social and economic impacts. However, most existing methods learn modal features from a single perspective, without considering simult...
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Similar question retrieval is a core task in community-based question answering (CQA) services. To balance the effectiveness and efficiency, the question retrieval system is typically implemented as multi-stage ranker...
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