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On the Use of Deep Learning Models for Automatic Animal Classification of Native Species in the Amazon
Camera trap image analysis, although critical for habitat and species conservation, is often a manual, time-consuming, and expensive task. Thus,...
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kNN Join for Dynamic High-Dimensional Data: A Parallel Approach
The k nearest neighbor (kNN) join operation is a fundamental task that combines two high-dimensional databases, enabling data points in the User...
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Multi-level Storage Optimization for Intermediate Data in AI Model Training
As Transformer-based large models become the mainstream of AI training, the development of hardware devices (e.g., GPUs) cannot keep up with the...
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Take a Close Look at the Optimization of Deep Kernels for Non-parametric Two-Sample Tests
The maximum mean discrepancy (MMD) test with deep kernel is a powerful method to distinguish whether two samples are drawn from the same...
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Balanced Hop-Constrained Path Enumeration in Signed Directed Graphs
Hop-constrained path enumeration, which aims to output all the paths from two distinct vertices within the given hops, is one of the fundamental...
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Probabilistic Reverse Top-k Query on Probabilistic Data
Reverse top-k queries have received much attention from research communities. The result of reverse top-k queries is a set of objects, which had the...
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IFGNN: An Individual Fairness Awareness Model for Missing Sensitive Information Graphs
Graph neural networks (GNNs) provide an approach for analyzing complicated graph data for node, edge, and graph-level prediction tasks. However, due...
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Discovering Densest Subgraph over Heterogeneous Information Networks
Densest Subgraph Discovery (DSD) is a fundamental and challenging problem in the field of graph mining in recent years. The DSD aims to determine,...
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Influence Maximization Revisited
Influence Maximization (IM) has been extensively studied, which is to select a set of k seed users from a social network to maximize the expected...
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Maximum Fairness-Aware (k, r)-Core Identification in Large Graphs
Cohesive subgraph mining is a fundamental problem in attributed graph analysis. The k-core model has been widely used in many studies to measure the...
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Spatial Shrinkage Prior: A Probabilistic Approach to Model for Categorical Variables with Many Levels
One of the most commonly used methods to prevent overfitting and select relevant variables in regression models with many predictors is the penalized...
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The Importance of Knowing the Arrival Order in Combinatorial Bayesian Settings
We study the measure of order-competitive ratio introduced by Ezra et al. [16] for online algorithms in Bayesian combinatorial settings. In our...
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Nash Stability in Fractional Hedonic Games with Bounded Size Coalitions
We consider fractional hedonic games, a natural and succinct subclass of hedonic games able to model many real-world settings in which agents have to...
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Online Nash Welfare Maximization Without Predictions
The maximization of Nash welfare, which equals the geometric mean of agents’ utilities, is widely studied because it balances efficiency and fairness...
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Equilibrium Analysis of Customer Attraction Games
We introduce a game model called “customer attraction game” to demonstrate the competition among online content providers. In this model, customers...
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Target-Oriented Regret Minimization for Satisficing Monopolists
We study a robust monopoly pricing problem where a seller aspires to sell an item to a buyer. We assume that the seller, unaware of the buyer’s...
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Social Recommendation Using Deep Auto-encoder and Confidence Aware Sentiment Analysis
The development of online social networks has attracted increasing interest in social recommendation. On the other hand, recommender systems based on...
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Finding a Second Wind: Speeding Up Graph Traversal Queries in RDBMSs Using Column-Oriented Processing
Recursive queries and recursive derived tables constitute an important part of the SQL standard. Their efficient processing is important for many...
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Investigating the Perceived Usability of Entity-Relationship Quality Frameworks for NoSQL Databases
Quality assessment of data models can be a challenging task due to its subjective nature. For the schemaless, heterogeneous and diverse group of...