Due to their size and processing demands, Large Language Models (LLMs) are challenging to implement on edge devices with constrained resources, such as mobile phones and Internet of Things platforms. To address these ...
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We study infinite-horizon average-reward Markov decision processes (AMDPs) in the context of general function approximation. Specifically, we propose a novel algorithmic framework named Local-fitted Optimization with ...
In the digital era, cyberbullying is a growing concern that impacts the well-being of its victims. The rise of cyberbullying among social media users necessitates robust detection solutions. One of these solutions is ...
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Massive scale of transactions with critical requirements become popular for emerging businesses,especially in *** of the most representative applications is the promotional event running on Alibaba's platform on s...
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Massive scale of transactions with critical requirements become popular for emerging businesses,especially in *** of the most representative applications is the promotional event running on Alibaba's platform on some special dates,widely expected by global *** we have achieved significant progress in improving the scalability of transactional database systems(OLTP),the presence of contention operations in workloads is still one of the fundamental obstacles to performance *** reason is that the overhead of managing conflict transactions with concurrency control mechanisms is proportional to the amount of *** a consequence,generating contented workloads is urgent to evaluate performance of modern OLTP database *** we have kinds of standard benchmarks which provide some ways in simulating contentions,e.g.,skew distribution control of transactions,they can not control the generation of contention quantitatively;even worse,the simulation effectiveness of these methods is affected by the scale of *** in this paper we design a scalable quantitative contention generation method with fine contention granularity *** conduct a comprehensive set of experiments on popular opensourced DBMSs compared with the latest contention simulation method to demonstrate the effectiveness of our generation work.
This paper explores the application of Visual Question-Answering (VQA) technology, which combines computer vision and natural language processing (NLP), in the medical domain, specifically for analyzing radiology scan...
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This study aims to improve the accuracy of click-through rate prediction for push ads through machine learning methods. Using the dataset released by Tianchi, we synthesized basic user information, ad features and use...
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The authors show that ifΘ=(θ_(jk))is a 3×3 totally irrational real skewsymmetric matrix,whereθ_(jk)∈[0,1)for j,k=1,2,3,then for anyε>0,there existsδ>0 satisfying the following:For any unital C^(*)-alg...
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The authors show that ifΘ=(θ_(jk))is a 3×3 totally irrational real skewsymmetric matrix,whereθ_(jk)∈[0,1)for j,k=1,2,3,then for anyε>0,there existsδ>0 satisfying the following:For any unital C^(*)-algebra A with the cancellation property,strict comparison and nonempty tracial state space,any four unitaries u1,u2,u3,w∈A such that(1)■,wujw-1=uj-1,w2=1A for j,k=1,2,3;(2)τ(aw)=0 and■for all n∈N,all a∈C^(*)(u1,u2,u3),j,k=1,2,3 and all tracial statesτon A,where C^(*)(u1,u2,u3)is the C^(*)-subalgebra generated by u1,u2 and u3,there exists a 4-tuple of unitaries■in A such that■and■for j,k=1,2,*** above conclusion is also called that the rotation relations of three unitaries with the flip action is stable under the above conditions.
Accurate monitoring of urban waterlogging contributes to the city’s normal operation and the safety of residents’daily ***,due to feedback delays or high costs,existing methods make large-scale,fine-grained waterlog...
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Accurate monitoring of urban waterlogging contributes to the city’s normal operation and the safety of residents’daily ***,due to feedback delays or high costs,existing methods make large-scale,fine-grained waterlogging monitoring impossible.A common method is to forecast the city’s global waterlogging status using its partial waterlogging *** method has two challenges:first,existing predictive algorithms are either driven by knowledge or data alone;and second,the partial waterlogging data is not collected selectively,resulting in poor *** overcome the aforementioned challenges,this paper proposes a framework for large-scale and fine-grained spatiotemporal waterlogging monitoring based on the opportunistic sensing of limited bus *** framework follows the Sparse Crowdsensing and mainly comprises a pair of iterative predictor and *** predictor uses the collected waterlogging status and the predicted status of the uncollected area to train the graph convolutional neural *** combines both knowledge-driven and data-driven approaches and can be used to forecast waterlogging status in all regions for the upcoming *** selector consists of a two-stage selection procedure that can select valuable bus routes while satisfying budget *** experimental results on real waterlogging and bus routes in Shenzhen show that the proposed framework could easily perform urban waterlogging monitoring with low cost,high accuracy,wide coverage,and fine granularity.
In analytical queries,a number of important operators like JOIN and GROUP BY are suitable for parallelization,and GPU is an ideal accelerator considering its power of parallel ***,when data size increases to hundreds ...
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In analytical queries,a number of important operators like JOIN and GROUP BY are suitable for parallelization,and GPU is an ideal accelerator considering its power of parallel ***,when data size increases to hundreds of gigabytes,one GPU card becomes insufficient due to the small capacity of global memory and the slow data transfer between host and device.A straightforward solution is to equip more GPUs linked with high-bandwidth connectors,but the cost will be highly *** utilize unified memory(UM)produced by NVIDIA CUDA(Compute Unified Device Architecture)to make it possible to accelerate large-scale queries on just one GPU,but we notice that the transfer performance between host and UM,which happens before kernel execution,is often significantly slower than the theoretical *** important reason is that,in singleGPU environment,data processing systems usually invoke only one or a static number of threads for data copy,leading to an inefficient transfer which slows down the overall performance *** this paper,we present D-Cubicle,a runtime module to accelerate data transfer between host-managed memory and unified memory.D-Cubicle boosts the actual transfer speed dynamically through a self-adaptive *** our experiments,taking data transfer into account,D-Cubicle processes 200 GB of data on a single GPU with 32 GB of global memory,achieving 1.43x averagely and 2.09x maximally the performance of the baseline system.
Order is one of the main instruments to measure data. In this paper, we will therefore discuss difthe relationship between objects in (empirical) data. ferent means for measuring and ‘calculating’ with However, comp...
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