We study the problem of estimating the score function of an unknown probability distribution ρ∗ from n independent and identically distributed observations in d dimensions. Assuming that ρ∗ is subgaussian and has a ...
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Considering the difficulty of financial time series forecasting in financial aid, much of the current research focuses on leveraging big data analytics in financial services. One modern approach is to utilize "pr...
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Music recommendation algorithms, from the perspective of real-time, can be classified into two categories: offline recommendation algorithms and online recommendation algorithms. To improve music recommendation accura...
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Music recommendation algorithms, from the perspective of real-time, can be classified into two categories: offline recommendation algorithms and online recommendation algorithms. To improve music recommendation accuracy, especially for the new music(users have no historic listening records on it), and real-time recommendation ability, and solve the interest drift problem simultaneously, we propose a hybrid music recommendation model based on personalized measurement and game theory. This model can be separated into two parts: an offline recommendation part(OFFLRP) and an online recommendation part(ONLRP). In the offline part, we emphasize users personalization. We introduce two metrics named user pursue-novelty degree(UPND) and music popularity(MP) to improve the traditional items-based collaborative filtering algorithm. In the online part, we try to solve the interest drift problem, which is a thorny problem in the offline part. We propose a novel online recommendation algorithm based on game theory. Experiments verify that the hybrid music recommendation model has higher new music recommendation accuracy, decent dynamical personalized recommendation ability, and real-time recommendation capability, and can substantially mitigate the problem of interest drift.
Referring video object segmentation (RVOS) aims at segmenting an object in a video with its text description. The core of RVOS lies in the modal alignment between the vision and text. To improve the performance, most ...
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In social network applications,individual opinion is often influenced by groups,and most decisions usually reflect the majority’s *** imposes the group influence maximization(GIM) problem that selects k initial nodes...
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In social network applications,individual opinion is often influenced by groups,and most decisions usually reflect the majority’s *** imposes the group influence maximization(GIM) problem that selects k initial nodes,where each node belongs to multiple groups for a given social network and each group has a weight,to maximize the weight of the eventually activated *** GIM problem is apparently NP-hard,given the NP-hardness of the influence maximization(IM) problem that does not consider *** on activating groups rather than individuals,this paper proposes the complementary maximum coverage(CMC) algorithm,which greedily and iteratively removes the node with the approximate least group influence until at most k nodes *** the evaluation of the current group influence against each node is only approximate,it nevertheless ensures the success of activating an approximate maximum number of ***,we also propose the improved reverse influence sampling(IRIS) algorithm through fine-tuning of the renowned reverse influence sampling algorithm for ***,we carry out experiments to evaluate CMC and IRIS,demonstrating that they both outperform the baseline algorithms respective of their average number of activated groups under the independent cascade(IC)model.
In order to classify the Cleveland Heart Disease dataset, this study evaluates the performance of three optimization methods, namely Fruit Fly Optimization (FFO), Particle Swarm Optimization (PSO), and Grey Wolf Optim...
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Graphs that are used to model real-world entities with vertices and relationships among entities with edges,have proven to be a powerful tool for describing real-world problems in *** most real-world scenarios,entitie...
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Graphs that are used to model real-world entities with vertices and relationships among entities with edges,have proven to be a powerful tool for describing real-world problems in *** most real-world scenarios,entities and their relationships are subject to constant *** that record such changes are called dynamic *** recent years,the widespread application scenarios of dynamic graphs have stimulated extensive research on dynamic graph processing systems that continuously ingest graph updates and produce up-to-date graph analytics *** the scale of dynamic graphs becomes larger,higher performance requirements are demanded to dynamic graph processing *** the massive parallel processing power and high memory bandwidth,GPUs become mainstream vehicles to accelerate dynamic graph processing ***-based dynamic graph processing systems mainly address two challenges:maintaining the graph data when updates occur(i.e.,graph updating)and producing analytics results in time(i.e.,graph computing).In this paper,we survey GPU-based dynamic graph processing systems and review their methods on addressing both graph updating and graph *** comprehensively discuss existing dynamic graph processing systems on GPUs,we first introduce the terminologies of dynamic graph processing and then develop a taxonomy to describe the methods employed for graph updating and graph *** addition,we discuss the challenges and future research directions of dynamic graph processing on GPUs.
Cognitive load while walking plays a role in safety, human-computer interaction, medicine, and other fields, and gait has been shown to have a robust connection with cognitive load. However, most studies on this issue...
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Coefficients learning has long been challenging in genetic programming based symbolic regression (GPSR). Recent GPSR methods employ Pearson correlation coefficient for fitness assessment with post-hoc linear scaling f...
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The field of Multimodal Sentiment Analysis (MSA) has recently witnessed an emerging direction seeking to tackle the issue of data incompleteness. Recognizing that the language modality typically contains dense sentime...
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