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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Gao, Xi Xiong, Jinxin Wang, Akang Duan, Qihong Xue, Jiang Shi, Qingjiang School of Mathematics and Statistics Xi'an Jiaotong University Xi'an China Shenzhen Research Institute of Big Data China School of Data Science The Chinese University of Hong Kong Shenzhen China School of Software Engineering Tongji University Shanghai China

Solving constrained nonlinear programs (NLPs) is of great importance in various domains such as power systems, robotics, and wireless communication networks. One widely used approach for addressing NLPs is the interior point method (IPM). The most computationally expensive procedure in IPMs is to solve systems of linear equations via matrix factorization. Recently, machine learning techniques have been adopted to expedite classic optimization algorithms. In this work, we propose using Long Short-Term Memory (LSTM) neural networks to approximate the solution of linear systems and integrate this approximating step into an IPM. The resulting approximate NLP solution is then utilized to warm-start an interior point solver. Experiments on various types of NLPs, including Quadratic Programs and Quadratically Constrained Quadratic Programs, show that our approach can significantly accelerate NLP solving, reducing iterations by up to 60% and solution time by up to 70% compared to the default solver. © 2024 Neural information processing systems foundation. All rights reserved.

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Automatic extraction of lightweight and efficient neural network architecture of heavy convolutional architectures to predict microsatellite instability from hematoxylin and eosin histology in gastric cancer

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Neural Computing and Applications 2024年第25期36卷 15295-15321页

作者： Rostami, Habib Ashkpour, Maryam Behzadi-Khormouji, Hamed Mokhtari, Maral Khayati, Armin Keshavarz, Ahmad Talatian Azad, Saeed Tabesh, Yahya Computer Engineering Department Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr75168 Iran Artificial Intelligence and Intelligent Healthcare Lab Artificial Intelligence and Data Mining Research Group Faculty of Intelligent Systems Engineering and Data Science ICT Research Institute Persian Gulf University Bushehr75168 Iran Faculty of New Science and Technologies University of Tehran Tehran Iran Department of Computer Science Imec-IDLab University of Antwerp Sint-Pietersvliet 7 Antwerp2000 Belgium Shahid Faghihi Hospital Shiraz University of Medical Sciences Shiraz Iran Department of Computer Science Engineering and IT School of Electrical and Computer Engineering Shiraz University Shiraz Iran Electrical Engineering Department Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr75168 Iran IoT and Signal Processing Research Group Faculty of Intelligent Systems Engineering and Data Science ICT Research Institute Persian Gulf University Bushehr75168 Iran Department of Mathematical Sciences Sharif University of Technology Tehran Iran

Cancers have emerged as a significant concern due to their impact on public health and society. The examination and interpretation of tissue sections stained with Hematoxylin and Eosin (H&E) play a crucial role in disease assessment, particularly in cases like gastric cancer. Microsatellite instability (MSI) is suggested to contribute to the carcinogenesis of specific gastrointestinal tumors. However, due to the nonspecific morphology observed in H&E-stained tissue sections, MSI determination often requires costly evaluations through various molecular studies and immunohistochemistry methods in specialized molecular pathology laboratories. Despite the high cost, international guidelines recommend MSI testing for gastrointestinal cancers. Thus, there is a pressing need for a new diagnostic modality with lower costs and widespread applicability for MSI detection. This study aims to detect MSI directly from H&E histology slides in gastric cancer, providing a cost-effective alternative. The performance of well-known deep convolutional neural networks (DCNNs) and a proposed architecture are compared. Medical image datasets are typically smaller than benchmark datasets like ImageNet, necessitating the use of off-the-shelf DCNN architectures developed for large datasets through techniques such as transfer learning. Designing an architecture proportional to a custom dataset can be tedious and may not yield desirable results. In this work, we propose an automatic method to extract a lightweight and efficient architecture from a given heavy architecture (e.g., well-known off-the-shelf DCNNs) proportional to a specific dataset. To predict MSI instability, we extracted the MicroNet architecture from the Xception network using the proposed method and compared its performance with other well-known architectures. The models were trained using tiles extracted from whole-slide images, and two evaluation strategies, tile-based and whole-slide image (WSI)-based, were employed and comp

关键词： Network architecture

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Evolution of defects and deformation mechanisms in different tensile directions of solidified lamellar Ti-Al alloy

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Chinese Physics B 2022年第4期31卷 518-524页

作者： Yutao Liu Tinghong Gao Yue Gao Lianxin Li Min Tan Quan Xie Qian Chen Zean Tian Yongchao Liang Bei Wang Institute of New Optoelectronic Materials and Technology College of Big Data and Information EngineeringGuizhou UniversityGuiyang 550025China College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China

Two-phaseγ-TiAl/α_(2)-Ti_(3)Al lamellar intermetallics have attracted considerable attention because of their excellent strength and ***,the exact deformation mechanisms remain to be *** this paper,a solidified lamellar Ti-Al alloy with lamellar orientation at 0°,17°,and 73°with respect to the loading direction was stretched by utilizing molecular dynamics(MD)*** results show that the mechanical properties of the sample are considerably influenced by solidified defects and tensile *** structure deformation and fracture were primarily attributed to an intrinsic stacking fault(ISF)accompanied by the nucleated Shockley dislocation,and the adjacent extrinsic stacking fault(ESF)and ISF formed by solidification tend to form large HCP structures during the tensile process loading at 73°.Moreover,cleavage cracking easily occurs on theγ/α_(2)interface under tensile *** fracture loading mechanism at 17°is grain boundary slide whereas,at 73°and 0°,the dislocation piles up to form a dislocation junction.

关键词： molecular dynamics simulation solidified lamellar Ti-Al alloy tensile directions γ/α_(2)interface

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CCTG-NET: Contextualized Convolutional Transformer-GRU Network for speech emotion recognition

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International Journal of Speech Technology 2023年第4期26卷 1099-1116页

作者： Tellai, Mohammed Mao, Qirong Department of Computer Science and Communication Engineering Jiangsu University Jiangsu Province Zhenjiang212013 China Jiangsu Engineering Research Center of Big Data Ubiquitous Perception and Intelligent Agriculture Applications Jiangsu Province Zhenjiang212013 China

Speech is a crucial aspect of human-to-human interactions and plays a fundamental role in the advancement of human–computer interaction (HCI) systems. Developing an accurate speech emotion recognition (SER) system for human conversations poses a critical yet challenging task. Existing state-of-the-art (SOTA) research in SER primarily focuses on modeling vocal information within individual conversational speech utterances, overlooking the significance of incorporating transactional information from the interaction context. In this paper, we present a novel Contextualized Convolutional Transformer-GRU Network (CCTG-Net) for recognizing speech emotions using Mel-spectrogram features, effectively integrating contextual information for emotion recognition. Our experiments are conducted on the widely-used emotional benchmark dataset, IEMOCAP. Compared to SOTA methods in four-class emotion recognition, our proposed model achieves a weighted accuracy of 88.4% and an unweighted accuracy (UA) of 89.1%. This marks a substantial 3.0% enhancement in UA while maintaining an optimal balance between performance and complexity. © 2023, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Emotion Recognition

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Multi-trial Vector-based Whale Optimization Algorithm

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Journal of Bionic engineering 2024年第3期21卷 1465-1495页

作者： Mohammad H.Nadimi-Shahraki Hajar Farhanginasab Shokooh Taghian Ali Safaa Sadiq Seyedali Mirjalili Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityNajafabad***Iran Big Data Research Center Najafabad BranchIslamic Azad UniversityNajafabad***Iran Department of Computer Science Nottingham Trent UniversityNottinghamNG118NSUK Centre for Artificial Intelligence Research and Optimisation Torrens UniversityBrisbane4006Australia

The Whale Optimization Algorithm(WOA)is a swarm intelligence metaheuristic inspired by the bubble-net hunting tactic of humpback *** spite of its popularity due to simplicity,ease of implementation,and a limited number of parameters,WOA’s search strategy can adversely affect the convergence and equilibrium between exploration and exploitation in complex *** address this limitation,we propose a new algorithm called Multi-trial Vector-based Whale Optimization Algorithm(MTV-WOA)that incorporates a Balancing Strategy-based Trial-vector Producer(BS_TVP),a Local Strategy-based Trial-vector Producer(LS_TVP),and a Global Strategy-based Trial-vector Producer(GS_TVP)to address real-world optimization problems of varied degrees of ***-WOA has the potential to enhance exploitation and exploration,reduce the probability of being stranded in local optima,and preserve the equilibrium between exploration and *** the purpose of evaluating the proposed algorithm's performance,it is compared to eight metaheuristic algorithms utilizing CEC 2018 test ***,MTV-WOA is compared with well-stablished,recent,and WOA variant *** experimental results demonstrate that MTV-WOA surpasses comparative algorithms in terms of the accuracy of the solutions and convergence ***,we conducted the Friedman test to assess the gained results statistically and observed that MTV-WOA significantly outperforms comparative ***,we solved five engineering design problems to demonstrate the practicality of *** results indicate that the proposed MTV-WOA can efficiently address the complexities of engineering challenges and provide superior solutions that are superior to those of other algorithms.

关键词： Swarm intelligence algorithms Metaheuristic algorithms Optimization engineering design problems Whale optimization algorithm

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Investigating the 3D cardiomyocyte arrangement in human interventricular septum sample using X-ray phase-contrast microtomography 17

Investigating the 3D cardiomyocyte arrangement in human inte...

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17th IEEE International Conference on Signal Processing, ICSP 2024

作者： Li, Wenfeng Li, Zhaorui Du, Yongbin Wang, Shunli Zhengzhou University of Science and Technology Institute of Big Data and Artificial Intelligence Zhengzhou China Harbin Institute of Technology School of Instrumentation Science and Engineering Harbin China Heilongjiang University of Science and Technology School of Electrical and Control Engineering Harbin China

ISBN: (纸本)9798350387384

A good knowledge of the three-dimensional cardiomyocyte arrangement in interventricular septum is crucial for understanding both ventricle's functions. In this preliminary study, we investigate the local myocardial architecture in a human interventricular septum sample imaged by X-ray phase-contrast micro-tomography. This imaging modality allows us to visualize the complex structure of myocardial tissue at high resolution. We first cut the reconstruction data into sub-volume of 32×32×32 voxels (i.e. 112×112×112 μm3) in size, and compute the elevation angle of the local cardiomyocyte using Fast Fourier Transform based method. Then, we describe the distribution of cardiomyocyte elevation angle in the sample globally and locally. We note that, in part of regions, the running of cardiomyocyte aggregates is winding. Though the function of this specific cardiomyocyte arrangement manner is unclear, its existence is inspiring and merits further investigation. © 2024 IEEE.

关键词： Fast Fourier transforms

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Co-occurrence is not Factual Association in Language Models 38

Co-occurrence is not Factual Association in Language Models

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhang, Xiao Li, Miao Wu, Ji Department of Electronics Engineering Tsinghua University China Department of Electronics Engineering College of AI Tsinghua University Beijing National Research Center for Information Science and Technology Center for Big Data and Clinical Research Institute for Precision Medicine Tsinghua University China

Pretrained language models can encode a large amount of knowledge and utilize it for various reasoning tasks, yet they can still struggle to learn novel factual knowledge effectively from finetuning on limited textual demonstrations. In this work, we show that the reason for this deficiency is that language models are biased to learn word co-occurrence statistics instead of true factual associations. We identify the differences between two forms of knowledge representation in language models: knowledge in the form of co-occurrence statistics is encoded in the middle layers of the transformer model and does not generalize well to reasoning scenarios beyond simple question answering, while true factual associations are encoded in the lower layers and can be freely utilized in various reasoning tasks. Based on these observations, we propose two strategies to improve the learning of factual associations in language models. We show that training on text with implicit rather than explicit factual associations can force the model to learn factual associations instead of co-occurrence statistics, significantly improving the generalization of newly learned knowledge. We also propose a simple training method to actively forget the learned co-occurrence statistics, which unblocks and enhances the learning of factual associations when training on plain narrative text. On both synthetic and real-world corpora, the two proposed strategies improve the generalization of the knowledge learned during finetuning to reasoning scenarios such as indirect and multi-hop question answering. © 2024 Neural information processing systems foundation. All rights reserved.

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Liquid metal assistant self-propagating high-temperature synthesis of S-containing high-entropy MAX-phase materials

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材料科学技术（英文版） 2025年第6期209卷 1-8页

作者： Donglong Bai Qiang Wang Bin Deng Yang Li Ao Huang Zitong Cheng Yun Zhao Jing Li Wei Yao Jianguang Xu School of Materials and Energy Shanghai Key Laboratory of Engineering Materials Application and EvaluationShanghai Polytechnic UniversityShanghai 201209China Shanghai Thermophysical Properties Big Data Professional Technical Service Platform Shanghai Engineering Research Center of Advanced Thermal Functional MaterialsShanghai 201209China School of Materials Science and Engineering Yancheng Institute of TechnologyYancheng 224000China School of Materials and Energy Shanghai Key Laboratory of Engineering Materials Application and EvaluationShanghai Polytechnic UniversityShanghai 201209China

Due to their high-entropy effects,the high-entropy(HE)MAX-phase materials improve the comprehen-sive performance of MAX phases,opening up more possibilities for practical engineering ***,it is still challenging to obtain S-containing high-entropy MAX phases because of the high volatilization behavior of sulfur,suffering from issues such as high reaction temperature and long re-action time of traditional synthesis *** paper proposes a novel process named as liquid metal assistant self-propagating high-temperature synthesis(LMA-SHS)for efficient synthesis of high-purity S-containing high-entropy MAX-phase ***-melting-point metal(Sn or In)has been introduced into the raw mixture and melted into a liquid phase during the early stage of the SHS *** serv-ing as a"binder"between transition metal atoms of the M-site due to the negative mixing enthalpy,this liquid phase can accelerate mass and heat transfer during the SHS process,ensuring a uniform solid solution of each element and realizing the synthesis of high-purity(TiNbVZr)2SC in an extremely short *** synthesis method for high-entropy MAX-phase materials developed in this study,i.e.,LMA-SHS,showing very short reaction time,low energy consumption,high yield,and low cost,has the promise to be a general energy-and resource-efficient route towards high-purity HE materials.

关键词： High-entropy S-containing MAX phases Liquid metal LMA-SHS

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Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers:A Life Course Perspective

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China CDC weekly 2024年第11期6卷 219-224,I0014-I0017页

作者： Cedric Zhang Bo Lua Yajie Gao Jinming Li Xingqi Cao Xinwei Lyu Yinuo Tu Shuyi Jin Zuyun Liu Center for Clinical Big Data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Healththe Key Laboratory of Intelligent Preventive Medicine of Zhejiang ProvinceZhejiang University School of MedicineHangzhou CityZhejiang ProvinceChina Institute of Epidemiology and Health Care University College LondonLondonUK College of Chemical and Biological Engineering Zhejiang UniversityHangzhou CityZhejiang ProvinceChina

Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of *** this study,we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English *** studies have predominantly used single biomarkers,such as C-reactive protein,or focused on specific life course stages and factors such as socioeconomic status,mental health,educational levels,and unhealthy *** summarizing the progress in this field,our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.

关键词： such insight directions

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AN ACCELERATED MANN-TYPE METHOD FOR SPLIT COMMON FIXED POINT PROBLEM IN HILBERT SPACES

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2024年第1期86卷 3-16页

作者： Yang, Lan Zhu, Li-Jun Postolache, Mihai School of Mathematics and Information Science North Minzu University Yinchuan750021 China The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province North Minzu University Yinchuan750021 China Bucharest060042 Romania Health Big Data Research Institute of North Minzu University Yinchuan750021 China Gheorghe Mihoc-Caius Iacob Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest050711 Romania

In this paper, we introduce a new method to solve split common fixed point problem of demicontractive operators in Hilbert spaces, which is based on the Wang method, inertial method and Mann method. Strong convergence result of the suggested algorithm is proved, and our results are utilized to study split feasibility problem and split variational inequality problem in Hilbert spaces. Finally, we compare the convergence speed of our algorithm with the Wang algorithm by a numerical example. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Hilbert spaces

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