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检索条件"任意字段=Conference on High Performance Computer Modernization Program"

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Extended Optimal Control Problem for Practical Application 4th

Extended Optimal Control Problem for Practical Application

引用

4th International conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Diveev, Askhat Shmalko, Elizaveta Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031812408

To apply a solution of the optimal control problem directly to the control object for which model this problem was solved, it is necessary to build a system of motion stabilization along the obtained optimal trajectory. However, the construction of such a stabilization system is not provided in the classical formulation of the optimal control problem. Therefore, additional requirements for the properties of the optimal solution have been introduced into the optimal control problem. A formulation of the extended optimal control problem is introduced and the approaches to its numerical solution are discussed. One way to meet the introduced requirements is to build a stabilization motion system of an object along a program trajectory. As far as stabilization to the whole program trajectory, not from point to point on this trajectory, is rather challenging task, so for this, numerical methods of symbolic regression are proposed to be applied. The approach consists in application of machine learning by symbolic regression to the control synthesis problem. Symbolic regression allows to find a mathematical expression for control function as a function of the state space vector. Computational example of solving the extended optimal control problem for a robot group is presented. It is shown experimentally, that the solution of the extended optimal control problem is much less sensitive to disturbances, than a direct solution of the classical optimal control problem. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Stabilization

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Leveraging Large Language Models for Flexible and Robust Table-to-Text Generation 35th

Leveraging Large Language Models for Flexible and Robust Tab...

引用

35th International conference on Database and Expert Systems Applications (DEXA)

作者： Oro, Ermelinda De Grandis, Luca Granata, Francesco Maria Ruffolo, Massimo CNR Inst High Performance Comp & Networking Via P Bucci 8-9C I-87036 Arcavacata Di Rende CS Italy Univ Calabria TechNest Start Incubator Altilia Srl Piazza Vermicelli I-87036 Arcavacata Di Rende CS Italy

ISBN: (纸本)9783031683084;9783031683091

Generating natural language descriptions from structured tabular data is a crucial challenge with high-impact applications across diverse domains, including business intelligence, scientific communication, and data analytics. Traditional rule-based and machine learning approaches have faced limitations in reusability, vocabulary coverage, and handling complex table layouts. Recent advances in LLMs pre-trained on vast corpora offer an opportunity to overcome these limitations by leveraging their strong language understanding and generation capabilities in a flexible learning setup. In this paper, We conduct a comprehensive evaluation of two LLMs - GPT-3.5 and LLaMa2-7B - on table-to-text generation across three diverse public datasets: WebNLG, NumericNLG, and ToTTo. Our experiments investigate both zero-shot prompting techniques and finetuning using the parameter-efficient LoRA method. Results demonstrate GPT-3.5's impressive capabilities, outperforming LLaMa2 in zero-shot settings. However, finetuning LLaMa2 on a subset of data significantly bridges this performance gap and produces generations much closer to ground truth and comparable to SOTA approaches. Our findings highlight LLMs' promising potential for data-to-text while identifying key areas for future research.

关键词： Natural Language Generation Table-to-Text Data-to-Text LLM Zero-Shot GPT-3 LLaMa Prompt Finetuning LoRA

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program Synthesis with Genetic programming: The Influence of Batch Sizes 1

引用

25th European conference on Genetic programming (EuroGP) Held as Part of EvoStar conference

作者： Sobania, Dominik Rothlauf, Franz Johannes Gutenberg Univ Mainz Mainz Germany

ISBN: (数字)9783031020568

ISBN: (纸本)9783031020568;9783031020551

Genetic programming is a method to generate computer programs automatically for a given set of input/output examples that define the user's intent. In real-world software development this method could also be used, as a programmer could first define the input/output examples for a certain problem and then let genetic programming generate the functional source code. However, a prerequisite for using genetic programming as support system in real-world software development is a high performance and generalizability of the generated programs. For some program synthesis benchmark problems, however, the generalizability to previously unseen test cases is low especially when lexicase is used as parent selection method. Therefore, we combine in this paper lexicase selection with small batches of training cases and study the influence of different batch sizes on the program synthesis performance and the generalizability of programs generated with genetic programming For evaluation, we use three common program synthesis benchmark problems. We find that the selection pressure can be reduced even when small batch sizes are used. Moreover, we find that, compared to standard lexicase selection, the obtained success rates on the test set are similar or even better when combining lexicase with small batches. Furthermore, also the generalizability of the found solutions can often be improved.

关键词： program synthesis Genetic programming Generalization

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high-performance integral imaging based light field 3D display 15

High-performance integral imaging based light field 3D displ...

引用

15th conference on Advances in Display Technologies

作者： Chen, Yuang Zhao, Chongji Bai, Yucheng Deng, Huan Sichuan Univ Coll Elect & Informat Engn Chengdu 610065 Peoples R China

ISBN: (纸本)9781510685246;9781510685253

Integral imaging based light field display reproduces vivid 3D images by reconstructing the light ray distributions of 3D scenes and is considered as one of the most promising true 3D display techniques due to its advantages of compact form factor and viewing comfort. However, integral imaging still faces challenges such as complex light field data acquisition and generation, and unsatisfactory display effects. We proposed a high-performance integral imaging 3D display method that included optimal voxel space selection, design of anisotropic backlighting, and error correction. In the display space, the distribution characteristics of voxel space in integral imaging were revealed, and a display scheme based on optimal voxel space was proposed. In terms of hardware structure, a display system with sub-pixel anisotropic backlighting was designed to address voxel aliasing and separation issues. For error correction, a sub-pixel marking technology was proposed to measure the axial position error of lenses with high precision, and a depth-based sub-pixel correction technology was employed to eliminate voxel drift. The proposed method eliminated the problems of voxel separation and aliasing, fully considered the performance of display devices, corrected the axial position errors of lenses, and effectively enhanced the quality of 3D images. These proposed methods make the integral imaging display device have high display performance, and has broad application prospects in many fields such as human-computer interaction, commercial displays, and medical applications.

关键词： light field display integral imaging voxel space sub-pixel marking voxel aliasing voxel separation

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Boosting Constrained Horn Solving by Unsat Core Learning 25th

Boosting Constrained Horn Solving by Unsat Core Learning

引用

25th International conference on Verification, Model Checking, and Abstract Interpretation (VMCAI)

作者： Abdulla, Parosh Aziz Liang, Chencheng Ruemmer, Philipp Uppsala Univ Uppsala Sweden Univ Regensburg Regensburg Germany

ISBN: (纸本)9783031505232;9783031505249

The Relational Hyper-Graph Neural Network (R-HyGNN) was introduced in [1] to learn domain-specific knowledge from program verification problems encoded in Constrained Horn Clauses (CHCs). It exhibits high accuracy in predicting the occurrence of CHCs in counterexamples. In this research, we present an R-HyGNN-based framework called MUSHyperNet. The goal is to predict the Minimal Unsatisfiable Subsets (MUSes) (i.e., unsat core) of a set of CHCs to guide an abstract symbolic model checking algorithm. In MUSHyperNet, we can predict the MUSes once and use them in different instances of the abstract symbolic model checking algorithm. We demonstrate the efficacy of MUSHyperNet using two instances of the abstract symbolic modelchecking algorithm: Counter-Example Guided Abstraction Refinement (CEGAR) and symbolic model-checking-based (SymEx) algorithms. Our framework enhances performance on a uniform selection of benchmarks across all categories from CHC-COMP, solving more problems (6.1% increase for SymEx, 4.1% for CEGAR) and reducing average solving time (13.3% for SymEx, 7.1% for CEGAR).

关键词： Automatic program verification Constrained Horn clauses Graph Neural Networks

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Select-Sliced Wasserstein Distance for Point Cloud Learning 11

Select-Sliced Wasserstein Distance for Point Cloud Learning

引用

International conference in 3D Vision (3DV)

作者： Du, Bang Chen, Kunyao Zhang, Haochen Nguyen, Truong Univ Calif San Diego La Jolla CA 92093 USA

ISBN: (纸本)9798350362466;9798350362459

Quantifying the discrepancy between point sets is a critical component for point cloud learning tasks. The mainstream point cloud learning tasks utilize Chamfer distance and Earth-Mover's distance. Chamfer distance is computationally efficient but may not fully capture differences between sets of points. Earth-Mover's distance, while precise, is computationally expensive and can be impractical to use with high-definition data. Several variants of SlicedWasserstein distances (SW) are introduced to reduce the computation cost, but bring new problems to the situation: The vanilla SW treats sampled slices equally, resulting in redundant projections;Distributional SlicedWasserstein distance requires gradient-based optimization, offsetting its benefits. To overcome this limitation and leverage the advantages of Sliced Wasserstein distance over EMD, we propose a novel metric, Select-Sliced Wasserstein distance. This new distance analyzes drawn samples of slices and quantifies their informativeness for each point in a single shot, which eliminates unnecessary projections as well as costly optimizations, but perpetuates the performance. Extensive experiments on various point cloud learning tasks to demonstrate the efficiency and effectiveness of the proposed distance metric. Our code is available at https://***/VideoProcessingLab/SSW_Distance

关键词： computer vision

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Process resource usage anomaly detection method based on process call stack in Linux Server 6

Process resource usage anomaly detection method based on pro...

引用

6th International conference on Artificial Intelligence and Pattern Recognition, AIPR 2023

作者： Liu, Bing Xie, Ruilian Chen, Lijun School of Computer Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

The call stack is a trace of function calls when a program is running. By analyzing the call stack, we can learn the execution path of the program, the relationship between functions and the number of function calls, which is of great significance for program optimization and troubleshooting. However, the call stack information is often very large, especially in complex application scenarios, the analysis and processing efficiency is very low, or even impossible to complete. Therefore, efficient statistics and analysis tools for the call stack are particularly important. This paper proposes an resource usage anomaly detection scheme for process behavior based on call stack coding and anomaly detection algorithm. It obtains the call stack by eBPF technology and establishes a hash table by map mechanism. It samples the call stack codes of all processes running in the machine at a specific frequency during the detection, and records the number of samples and execution time of each different call stack code. A user mode program reads data from the buffer. The call stack statistics is analyzed in user space, and the abnormal number of process call stacks is found by anomaly detection algorithm every period of time, which is convenient to find the call bottleneck of the machine causing high load. The abnormal call stacks are used to optimize the program and improve the performance of the machine, and are compatible with the data collected by Perf. The tool is efficient, accurate, scalable, and can quickly locate performance problems in the production environment. © 2023 ACM.

关键词： Anomaly detection

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Pathfinder: high-Resolution Control-Flow Attacks Exploiting the Conditional Branch Predictor 24

Pathfinder: High-Resolution Control-Flow Attacks Exploiting ...

引用

29th ACM International conference on Architectural Support for programming Languages and Operating Systems, ASPLOS 2024

作者： Yavarzadeh, Hosein Agarwal, Archit Christman, Max Garman, Christina Genkin, Daniel Kwong, Andrew Moghimi, Daniel Stefan, Deian Taram, Kazem Tullsen, Dean UC San Diego United States UNC Chapel Hill United States Purdue University United States Georgia Tech United States Google United States

ISBN: (纸本)9798400703867

This paper introduces novel attack primitives that enable adversaries to leak (read) and manipulate (write) the path history register (PHR) and the prediction history tables (PHTs) of the conditional branch predictor in high-performance CPUs. These primitives enable two new classes of attacks: first, it can recover the entire control flow history of a victim program by exploiting read primitives, as demonstrated by a practical secret-image recovery based on capturing the entire control flow of libjpeg routines. Second, it can launch extremely high-resolution transient attacks by exploiting write primitives. We demonstrate this with a key recovery attack against AES based on extracting intermediate values. © 2024 Copyright held by the owner/author(s).

关键词： program processors

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Heterogeneous network impulsive dynamics for identifying disease-associated genes

Heterogeneous network impulsive dynamics for identifying dis...

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2024 IEEE International conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Xiang, Ju Chen, Shengkai Wang, Lin-Cong-Hua Meng, Xiangmao Li, Min Changsha University of Science and Technology School of Computer and Communication Engineering Changsha China Central South University School of Computer Science and Engineering Changsha China Xiangtan University School of Computer Science Xiangtan China

ISBN: (纸本)9798350386226

Identifying disease-associated genes (DAGs) is important for the research of complex diseases, and network-based methods have been a powerful and elegant strategy for this topic. Genes and their products perform biological functions through synergy in biological networks, but mining useful information from the networks remains an open issue. Therefore, we propose a novel heterogeneous network impulsive dynamics model to identify DAGs more effectively. It inspires a heterogeneous network impulsive dynamical process by imposing impulsive signals at specific nodes, in an enhanced dual-layer heterogeneous network. Then, it extracts the impulsive dynamical signatures of responses of nodes to the impulsive signals so as to infer DAGs. A series of experiments confirm that this model has good performance of inferring DAGs under different conditions, and case studies further demonstrate its effectiveness. Furthermore, a user-friendly web platform is provided to facilitate prioritization and analysis of DAGs. It may become a useful tool for studying complex diseases and relevant genes. © 2024 IEEE.

关键词： Genome

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A MIMO Detector Utilizing DNN for Faster-Than-Nyquist Optical Wireless Communications 15

A MIMO Detector Utilizing DNN for Faster-Than-Nyquist Optica...

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15th IEEE International conference on Advanced Infocomm Technology, ICAIT 2023

作者： Cao, Minghua Yao, Ruifang Sun, Qinxue Zhang, Yue Yang, Qing Wang, Huiqin Lanzhou University of Technology School of Computer and Communication Lanzhou China

ISBN: (纸本)9798350314120

Traditional multiple input multiple output (MIMO) detection algorithms encounter challenges with computational complexity and performance limitations when dealing with high-dimensional inputs and complex channel conditions. To improve the precision of signal recovery in atmospheric turbulence channels for faster-than-Nyquist (FTN) optical wireless communication (OWC) systems, a deep learning (DL) based MIMO detector is proposed. By utilizing a deep neural network (DNN), nonlinear mappings in MIMO systems can be learned, leading to improved detection performance and reduced computational overhead. Simulation results demonstrate that our proposed DNN detector can achieve comparable performance to the maximum likelihood (ML) method and the complexity is reduced by 37% compared with the ML. © 2023 IEEE.

关键词： Deep neural networks

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