435 research outputs found

    Reducing Communication for Split Learning by Randomized Top-k Sparsification

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    Split learning is a simple solution for Vertical Federated Learning (VFL), which has drawn substantial attention in both research and application due to its simplicity and efficiency. However, communication efficiency is still a crucial issue for split learning. In this paper, we investigate multiple communication reduction methods for split learning, including cut layer size reduction, top-k sparsification, quantization, and L1 regularization. Through analysis of the cut layer size reduction and top-k sparsification, we further propose randomized top-k sparsification, to make the model generalize and converge better. This is done by selecting top-k elements with a large probability while also having a small probability to select non-top-k elements. Empirical results show that compared with other communication-reduction methods, our proposed randomized top-k sparsification achieves a better model performance under the same compression level.Comment: Accepted by IJCAI 202

    Research on wear prediction of piston/cylinder pair in axial piston pumps

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    The piston/cylinder pair is the critical lubricating interface of axial piston pumps. It suffers from excessive wear, especially under high output pressure. The performance degradation of the piston/cylinder pair is significant to be clarified. In this paper, a wear prediction method of the piston/cylinder pair is established by coupling the load-bearing and lubrication parameters calculation model and the wear calculation model. The models are validated through experiments. The experimental and simulated results show that the wear of two ends of the cylinder bore is severe in the specific ranges of circumferential angle. The time-varying wear process of the piston/cylinder pair can be obtained by using this method; therefore, the maintenance time can be predicted

    Pushing the Limits of ChatGPT on NLP Tasks

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    Despite the success of ChatGPT, its performances on most NLP tasks are still well below the supervised baselines. In this work, we looked into the causes, and discovered that its subpar performance was caused by the following factors: (1) token limit in the prompt does not allow for the full utilization of the supervised datasets; (2) mismatch between the generation nature of ChatGPT and NLP tasks; (3) intrinsic pitfalls of LLMs models, e.g., hallucination, overly focus on certain keywords, etc. In this work, we propose a collection of general modules to address these issues, in an attempt to push the limits of ChatGPT on NLP tasks. Our proposed modules include (1) a one-input-multiple-prompts strategy that employs multiple prompts for one input to accommodate more demonstrations; (2) using fine-tuned models for better demonstration retrieval; (3) transforming tasks to formats that are more tailored to the generation nature; (4) employing reasoning strategies that are tailored to addressing the task-specific complexity; (5) the self-verification strategy to address the hallucination issue of LLMs; (6) the paraphrase strategy to improve the robustness of model predictions. We conduct experiments on 21 datasets of 10 representative NLP tasks, including question answering, commonsense reasoning, natural language inference, sentiment analysis, named entity recognition, entity-relation extraction, event extraction, dependency parsing, semantic role labeling, and part-of-speech tagging. Using the proposed assemble of techniques, we are able to significantly boost the performance of ChatGPT on the selected NLP tasks, achieving performances comparable to or better than supervised baselines, or even existing SOTA performances

    Safeguarding authenticity versus innovative development: methods of protecting traditional Chinese martial arts

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    This article reflects on the conflict between the two main viewpoints of the protection of Chinese martial arts culture and defines the two protection methods of “Safeguarding Authenticity” and “Innovative Development”. This article aims to enhance the vitality and cultural heritage of traditional Chinese martial arts and discusses the protection and development of traditional Chinese martial arts from the perspective of folklore intangible cultural heritage (ICH) protection. Studies indicate that to continue the development of traditional Chinese martial arts from generation to generation, it must adapt to the laws of current social and cultural development. With the goal of improving the vitality of traditional martial arts culture, on the basis of adhering to the inheritance of the core skills of traditional martial arts, it advocates an innovative development mode that keeps pace with the times. Its fundamental purpose is to enable the sustainable and healthy development of traditional martial arts

    Fabrication of micro-scale radiation shielding structures using tungsten nanoink through electrohydrodynamic inkjet printing

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    Electronics components used in space and strategic missions are exposed to harsh radiation environments, which could cause operational malfunction of the system through lattice displacement or ionization effects. One potential solution is to use tungsten as radiation shielding. Tungsten is a very effective material in shielding electronic components and manufacturing gratings for x-ray imaging. However, intrinsic properties of tungsten (e.g. density, chemical/thermal inertness and hardness) post a significant challenge of fabricating the material into micro-scale and delicate structures, especially in electronic device fabrication. To address the problem, we designed a new tungsten nanoink and developed a straightforward approach to create tungsten micro-structures by 3D printing. Various microstructures down to 10 µm resolution have been patterned and fabricated by electrohydrodynamic inkjet (e-jet) printing using tungsten nanoink. By optimizing process parameters (voltage modality) and materials properties (ink formulation), the dimension and morphology of the structures can be precisely controlled. An AC-modulated voltage was employed during the e-jet printing process to make the patterns much more controllable and stable. Multi-layer tungsten lines were characterized by x-ray imaging and exhibited excellent absorption of x-ray radiation. With the same thickness, printed lines showed nearly 1/3 absorptivity of x-ray radiation of bulk tungsten, leading to significant radiation attenuation effectiveness. Tungsten nanoink is a new material used in e-jet printing that has not been reported in the literature to the best of authors\u27 knowledge. The study establishes a new methodology of manufacturing micro-nano scale shielding components for electronic devices and rapid prototyping of gratings and collimators in radiography for medical and inspection applications. The research also provides practical guidance to fabricate high melting-point metals via nanoink and micro/nano scale 3D printing
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