Titlebook: Artificial Intelligence Applications and Innovations; 6th IFIP WG 12.5 Int Harris Papadopoulos,Andreas S. Andreou,Max Bramer Conference pro

Albinism

Tobias Ahlbrecht,Michael Winikoffetical guarantees on the cumulative losses of the algorithms. We kernelize one of the algorithms and prove theoretical guarantees on the loss of the kernelized version. We perform experiments and compare our algorithms with logistic regression.

Lipoprotein

弄污

敲竹杠

Agent EXPRI: Licence to Explain is performed with reference to their efficiency (overall computing demands) and robustness (capability to detect near-optimal solutions). The optimum design of a real-world overhead traveling crane is used as the test bed application for conducting optimization test runs.

Conquest

中子

Innovative Applications of Artificial Intelligence Techniques in Software Engineeringimited the application of AI techniques in many real world applications. This talk provides an insight into applications of AI techniques in software engineering and how innovative application of AI can assist in achieving ever competitive and firm schedules for software development projects as well

中世紀(jì)

Frequency-Range

The Importance of Similarity Metrics for Representative Users Identification in Recommender Systemse the scalability and diversity issues faced by most recommendation algorithms face. We show through extended evaluation experiments that cluster representative make successful recommendations outperforming the K-nearest neighbor approach which is common in recommender systems that are based on coll

Patrimony

An Optimal Scaling Approach to Collaborative Filtering Using Categorical Principal Component Analysilized recommendations. The most common and accurate approaches to CF are based on latent factor models. Latent factor models can tackle two fundamental problems of CF, data sparsity and scalability and have received considerable attention in recent literature. In this work, we present an optimal sca

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