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CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification 18th

CICA: Content-Injected Contrastive Alignment for Zero-Shot D...

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18th International Conference on Document Analysis and Recognition (ICDAR)

作者： Sinha, Sankalp Khan, Muhammad Saif Ullah Sheikh, Talha Uddin Stricker, Didier Afzal, Muhammad Zeshan RPTU Dept Comp Sci D-67663 Kaiserslautern Germany German Res Ctr Artificial Intelligence DFKI D-67663 Kaiserslautern Germany

ISBN: (纸本)9783031705458;9783031705465

Zero-shot learning has been extensively investigated in the broader field of visual recognition, attracting significant interest recently. However, the current work on zero-shot learning in document image classification remains scarce. The existing studies either focus exclusively on zero-shot inference, or their evaluation does not align with the established criteria of zero-shot evaluation in the visual recognition domain. We provide a comprehensive document image classification analysis in Zero-Shot Learning (ZSL) and Generalized Zero-Shot Learning (GZSL) settings to address this gap. Our methodology and evaluation align with the established practices of this domain. Additionally, we propose zero-shot splits for the RVL-CDIP dataset. Furthermore, we introduce CICA (pronounced "ki center dot ka"), a framework that enhances the zero-shot learning capabilities of CLIP. CICA consists of a novel 'content module' designed to leverage any generic document-related textual information. The discriminative features extracted by this module are aligned with CLIP's text and image features using a novel 'coupled-contrastive' loss. Our module improves CLIP's ZSL top-1 accuracy by 6.7% and GZSL harmonic mean by 24% on the RVL-CDIP dataset. Our module is lightweight and adds only 3.3% more parameters to CLIP. Our work sets the direction for future research in zero-shot document classification.

关键词： Document Image Classification Zero-Shot Learning Generalised Zero-Shot Learning Multimodal Learning

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DScope: To Reliably and Securely Acquire Live Data from Kernel-Compromised ARM Devices 28th

DScope: To Reliably and Securely Acquire Live Data from Kern...

引用

28th European Symposium on Research in computer Security (ESORICS)

作者： Chen, Zhe Qiu, Haiqing Ding, Xuhua Singapore Management Univ Singapore Singapore

ISBN: (纸本)9783031514814;9783031514821

Live data acquisition from a mobile device controlled by a corrupted kernel is challenging as the adversary can block data reporting from the inside and also sabotage external I/O interactions. This paper proposes DScope as a reliable live data acquisition system for ARM devices without trusting their kernels. It ensures that a device user can always launch DScope to securely extract the needed virtual memory data when the device is under attack. Besides its reliability, DScope also preserves kernel semantic and support user-customized acquisition routines. We have built a prototype of DScope on a Raspberry Pi 4 development board and have also tested DScope's reliability against various forms of denial of service attacks. Our experiments show that a user can dynamically import data acquisition routines to the device to extract kernel objects and runtime stacks from an attack scene or a kernel crashing site.

关键词： Data acquisition

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VM-Rec: A Variational Mapping Approach for Cold-Start User Recommendation 1

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8th International Joint Conference on Web and Big Data and Web-Age Information Management (APWeb-WAIM)

作者： Zheng, Linan Chen, Jiale Liu, Pengsheng Zhang, Guangfa Fang, Jinyun Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Guizhou Univ Coll Big Data & Informat Engn Guiyang Peoples R China

ISBN: (数字)9789819772353

ISBN: (纸本)9789819772346;9789819772353

The cold-start problem is a common challenge for most recommender systems. The practical application of most cold-start methods is hindered by the deficiency in auxiliary content information for users. Furthermore, most methods often require simultaneous updates to extensive parameters of recommender models, resulting in high training costs, especially in large-scale industrial scenarios. We observe that the model can generate expressive embeddings for warm users with relatively more interactions. Initially, these users were cold-start users, and after transitioning to warm users, they exhibit clustering patterns in their embeddings with consistent initial interactions. Motivated by this, we propose a Variational Mapping approach for cold-start user Recommendation (VM-Rec), mapping from few initial interactions to expressive embeddings for cold-start users. Specifically, we encode the initial interactions into a latent representation, where each dimension disentangledly signifies the degree of association with each warm user. Subsequently, we utilize this latent representation as the parameters for the mapping function, mapping (decoding) it into an expressive embedding, which can be integrated into a pre-trained recommender model directly. Our method is evaluated on three datasets, demonstrating superior performance compared to other popular cold-start methods (Code is available at https://***/Linan2018/VM-Rec.).

关键词： Cold-start Recommender systems Mapping approach

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Machine Learning Accelerated Prediction of 3D Granular Flows in Hoppers 33rd

Machine Learning Accelerated Prediction of 3D Granular Flows...

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33rd International Conference on Artificial Neural Networks and Machine Learning (ICANN)

作者： Le, Duy Linh Nguyen Phung, Truong Howard, David Kahandawa, Gayan Murshed, Manzur Delaney, Gary W. CSIRO Data61 Sydney NSW Australia Federat Univ Australia Mt Helen Vic Australia Deakin Univ Geelong Vic Australia

ISBN: (纸本)9783031723551;9783031723568

Granular materials are crucial components in a broad variety of industrial and natural processes. However, despite their widespread importance, predicting their complex flow behaviour under different conditions remains extremely challenging. The Discrete Element Method (DEM) is the primary computational technique used to simulate granular flows, and while it can produce highly accurate predictions, it is also inherently computationally expensive. We look to overcome this computational bottleneck through the use of a neural network surrogate model for 3D granular flow simulation, and consider the industrially important use case of flow in grain hoppers. We investigate our model performance across a range of different time scales, quantifying its accuracy and generalizability to different hopper geometries. The use of deep learning techniques for the prediction of granular flow dynamics offers an excellent opportunity for providing step change increases in computational efficiency for industrial decision-making and potential application in real-time decision making in diverse manufacturing settings.

关键词： Discrete Element Method Deep Neural Networks Granular Flow Industrial Machinery

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Technology for Social Connectedness: A Case Study in Academic Communal Spaces 23rd

Technology for Social Connectedness: A Case Study in Academi...

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23rd IFIP WG 6.11 Conference on e-Business, e-Services and e-Society (I3E)

作者： Ali, Gul Sher Giannakos, Michail Petersen, Sobah Abbas NTNU Dept Comp Sci Trondheim Norway

ISBN: (纸本)9783031722332;9783031722349

Students in the early stages of their studies are prone to isolation. This case study focuses on doctoral students and empirically investigates the potential of Information and Communication Technologies in academic communal spaces to enhance social connectedness. To do so, we conducted a qualitative exploratory study that employed semi-structured interviews. In particular, we interviewed 7 doctoral students and asked them about their understanding and perceptions of integrating technologies in communal spaces. We utilized brochures of fictional technologies and worksheets to probe and elucidate students' insights on social connectedness. The coding of the interview corpus suggested that technologies can significantly foster social connectedness by facilitating traditional socializing practices in the academic communal spaces. Additionally, data highlighted the preference for technologies that facilitate student collaboration in addressing academic and practical challenges while emphasizing the importance of incorporating privacy measures to foster positive interactions. This study contextualized the framework of social connectedness by operationalizing its dimensions-belongingness, social appraisal, and relationship salience. The implications of this research extend to educational policymakers, and technology developers, indicating that integrating technologies in communal areas mitigate feelings of isolation among doctoral students and develop inclusive communities.

关键词： Academic Communal Spaces Social Connectedness Information and Communication Technologies (ICT)

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Using a Spatial Grid Model to Interpret Players Movement in Field Sports 26th

Using a Spatial Grid Model to Interpret Players Movement in ...

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26th International Conference on Data Warehousing and Knowledge Discovery (DaWaK)

作者： Antonini, Valerio Scriney, Michael Mileo, Alessandra Roantree, Mark Dublin City Univ Sch Comp Dublin D09 V209 9 Ireland Dublin City Univ Insight SFI Res Ctr Data Analyt Sch Comp Dublin 9 Ireland

ISBN: (纸本)9783031683220;9783031683237

The global sports analytics industry has a market value of USD 3.78 billion in 2023. The increase of wearables such as GPS sensors has provided analysts with large fine-grained datasets detailing player performance. Traditional analysis of this data focuses on individual athletes with measures of internal and external loading such as distance covered in speed zones or rate of perceived exertion. However these metrics do not provide enough information to understand team dynamics within field sports. The spatio-temporal nature of match play necessitates an investment in date-engineering to adequately transform the data into a suitable format to extract features such as areas of activity. In this paper we present an approach to construct Time-Window Spatial Activity Graphs (TWGs) for field sports. Using GPS data obtained from Gaelic Football matches we demonstrate how our approach can be utilised to extract spatio-temporal features from GPS sensor data.

关键词： Investments

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On the Precision Loss in Approximate Homomorphic Encryption 30th

On the Precision Loss in Approximate Homomorphic Encryption

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30th Annual International Research Conference on Selected Areas in Cryptography (SAC)

作者： Costache, Anamaria Curtis, Benjamin R. Hales, Erin Murphy, Sean Ogilvie, Tabitha Player, Rachel Norwegian Univ Sci & Technol NTNU Trondheim Norway Zama Paris France Royal Holloway Univ London Egham Surrey England

ISBN: (纸本)9783031533679;9783031533686

Since its introduction at Asiacrypt 2017, the CKKS approximate homomorphic encryption scheme has become one of the most widely used and implemented homomorphic encryption schemes. Due to the approximate nature of the scheme, application developers using CKKS must ensure that the evaluation output is within a tolerable error of the corresponding plaintext computation. Choosing appropriate parameters requires a good understanding of how the noise will grow through the computation. A strong understanding of the noise growth is also necessary to limit the performance impact of mitigations to the attacks on CKKS presented by Li and Micciancio (Eurocrypt [34]). In this work, we present a comprehensive noise analysis of CKKS, that considers noise coming both from the encoding and homomorphic operations. Our main contribution is the first average-case analysis for CKKS noise, and we also introduce refinements to prior worst-case noise analyses. We develop noise heuristics both for the original CKKS scheme and the RNS variant presented at SAC 2018. We then evaluate these heuristics by comparing the predicted noise growth with experiments in the HEAAN and FullRNS-HEAAN libraries, and by comparing with a worst-case noise analysis as done in prior work. Our findings show mixed results: while our new analyses lead to heuristic estimates that more closely model the observed noise growth than prior approaches, the new heuristics sometimes slightly underestimate the observed noise growth. This evidences the need for implementation-specific noise analyses for CKKS, which recent work has shown to be effective for implementations of similar schemes.

关键词： Cryptography

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Distributed SMT Solving Based on Dynamic Variable-Level Partitioning 36th

Distributed SMT Solving Based on Dynamic Variable-Level Part...

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36th International Conference on computer-Aided Verification (CAV)

作者： Zhao, Mengyu Cai, Shaowei Qian, Yuhang Chinese Acad Sci Inst Software Key Lab Syst Software Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China

ISBN: (纸本)9783031656262;9783031656279

Satisfiability Modulo Theories on arithmetic theories have significant applications in many important domains. Previous efforts have been mainly devoted to improving the techniques and heuristics in sequential SMT solvers. With the development of computing resources, a promising direction to boost performance is parallel and even distributed SMT solving. We explore this potential in a divide-and-conquer view and propose a novel dynamic parallel framework with variable-level partitioning. To the best of our knowledge, this is the first attempt to perform variable-level partitioning for arithmetic theories. Moreover, we enhance the interval constraint propagation algorithm, coordinate it with Boolean propagation, and integrate it into our variable-level partitioning strategy. Our partitioning algorithm effectively capitalizes on propagation information, enabling efficient formula simplification and search space pruning. We apply our method to three state-of-the-art SMT solvers, namely CVC5, OpenSMT2, and Z3, resulting in efficient parallel SMT solvers. Experiments are carried out on benchmarks of linear and nonlinear arithmetic over both real and integer variables, and our variable-level partitioning method shows substantial improvements over previous partitioning strategies and is particularly good at non-linear theories.

关键词： Satisfiability Modulo Theories Parallel Computing Partitioning Strategy Interval Constraint Propagation

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New Characterizations of Full Convexity 3rd

New Characterizations of Full Convexity

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3rd International Joint Conference on Discrete Geometry and Mathematical Morphology (DGM)

作者： Feschet, Fabien Lachaud, Jacques-Olivier Univ Clermont Auvergne CNRS ENSMSE LIMOS F-63000 Clermont Ferrand France Univ Savoie Mt Blanc CNRS LAMA F-73000 Chambery France

ISBN: (纸本)9783031577925;9783031577932

Full convexity has been recently proposed as an alternative definition of digital convexity. In contrast to classical definitions, fully convex sets are always connected and even simply connected whatever the dimension, while remaining digitally convex in the usual sense. Several characterizations were proposed in former works, either based on lattice intersection enumeration with several convex hulls, or using the idempotence of an envelope operator. We continue these efforts by studying simple properties of real convex sets whose digital counterparts remain largely misunderstood. First we study if we can define full convexity through variants of the usual continuous convexity via segments inclusion, i.e. "for all pair of points of X, the straight segment joining them must lie within the set X". We show an equivalence of full convexity with this segment convexity in dimension 2, and counterexamples starting from dimension 3. If we consider now d-simplices instead of a segment (2-simplex), we achieve an equivalence in arbitrary dimension d. Secondly, we exhibit another characterization of full convexity, which is recursive with respect to the dimension and uses simple axis projections. This latter characterization leads to two immediate applications: a proof that digital balls are indeed fully convex, and a natural progressive measure of full convexity for arbitrary digital sets.

关键词： Digital geometry Digital convexity Full convexity

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A Branch and Price Algorithm for the Two-Agent Heterogeneous Fleet Vehicle Routing Problem with Time Windows 1

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20th International Conference on Intelligent Computing (ICIC)

作者： Li, Jie Yu, Nai-Kang Hu, Rong Zhang, Zi-Qi Kunming Univ Sci & Technol Sch Informat Engn & Automat Kunming 650500 Yunnan Peoples R China

ISBN: (数字)9789819755783

ISBN: (纸本)9789819755776;9789819755783

In this paper, a two-agent heterogeneous fleet vehicle routing problem with time windows (TAHF_VRPTW) is considered. The objective of the first agent is to minimize the total tardiness and the objective of the second agent is to minimize the total transportation cost. A new mixed integer programming model (MILP) is built for this problem, and then a new branch and price algorithm (NBAPA) is proposed to address it. In the NBAPA, a genetic algorithm (GA) is developed to construct the initial columns, and a label algorithm is designed to exactly solve sub-problems. If the optimal solution obtained by column generation contains real elements, this solution should be used for branch operation. Extensive computational experiments are conducted on the Solomon benchmark instances. The results show that within the specified time, compared with the standard BAP algorithm (i.e., theBAPwithout usingGAto generate initial columns), theNBAPA can reduce the computation time by an average of 28.32% and the average number of branches by 42.29%.

关键词： Heterogeneous fleets Label algorithm Vehicle routing Branch and Price Two-agent

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