Search
Search Results
-
Automated Negotiations Protocols for Complex Utility Function as Social System
This chapter focuses on automated negotiations based on multi-agent systems. It targets researchers and students in various communities of autonomous...
-
A residual utility-based concept for high-utility itemset mining
Knowledge discovery in databases aims at finding useful information for decision-making. The problem of high-utility itemset mining (HUIM) has...
-
A High Utility Co-location Pattern Mining Algorithm Using Multiple Utility Thresholds
High utility co-location pattern (HUCP) mining refers to discovering a group of spatial features from spatial data which the instances of the group...
-
Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization
In this paper, we introduce multi-objective deep centralized multi-agent actor-critic (MO-DCMAC), a multi-objective reinforcement learning method for...
-
Re-induction based mining for high utility item-sets
The High Utility Itemset mining (HUIM) is an important research area in the field of data mining and knowledge discovery. HUIM aims to discover the...
-
Novel stochastic algorithms for privacy-preserving utility mining
High-utility itemset mining (HUIM) is a technique for extracting valuable insights from data. When dealing with sensitive information, HUIM can raise...
-
Hypertasking: From Information Web to Computing Utility
John McCarthy proposed the vision of utility computing in 1961. Barbara Liskov proposed a related vision of abstraction-powered Internet Computer in...
-
Sponsored Search Auction Design Beyond Single Utility Maximization
Auction design for the modern advertising market has gained significant prominence in the field of game theory. With the recent rise of auto-bidding...
-
Utility-driven virtual machine allocation in edge cloud environments using a partheno-genetic algorithm
Mobile Edge Computing alleviates network congestion and reduces latency by offloading tasks to the network edge. However, fluctuating Quality of...
-
Balancing Privacy and Utility in Multivariate Time-Series Classification
In the modern era, characterized by the widespread presence of sensor-based systems, ensuring time-series data privacy without compromising utility...
-
Utility Functions and Visualizations
In this chapter, we explore the utility of several advanced functions available in PySpark. To enhance your understanding, we recommend reviewing the...
-
FaaS-Utility: Tackling FaaS Cold Starts with User-Preference and QoS-Driven Pricing
This study introduces FaaS-Utility, a novel approach aimed at optimizing Function-as-a-Service (FaaS) systems by addressing the critical issue of...
-
High utility itemset mining in data stream using elephant herding optimization
Mining high utility itemsets from data stream within limited time and space is a challenging task. Traditional algorithms typically require multiple...
-
Mining Regional High Utility Co-location Pattern
A co-location pattern is a set of spatial features whose instances are frequently located together in geo-space. In real world, different instances...
-
Enhancing Data Utility in Personalized Differential Privacy: A Fine-Grained Processing Approach
Personalized differential privacy (PDP) offers accurate privacy protection by considering individual differences and personalized privacy...
-
TKU-BChOA: an accurate meta-heuristic method to mine Top-k high utility itemsets
High utility itemset mining is an essential new task in data mining, which is obtained from the extension of frequent itemset mining problems. The...
-
Actor-critic multi-objective reinforcement learning for non-linear utility functions
We propose a novel multi-objective reinforcement learning algorithm that successfully learns the optimal policy even for non-linear utility...
-
An efficient PSO-based evolutionary model for closed high-utility itemset mining
High-utility itemset mining (HUIM) is a widely adopted data mining technique for discovering valuable patterns in transactional databases. Although...
-
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings
In this study, we tackle the problem of computing an expectation of ranking with the guarantee of the Pareto-optimal balance between (1) maximizing...
-
CG-FHAUI: an efficient algorithm for simultaneously mining succinct pattern sets of frequent high average utility itemsets
The identification of both closed frequent high average utility itemsets (CFHAUIs) and generators of frequent high average utility itemsets (GFHAUIs)...
