Albinism 发表于 2025-3-28 15:38:43
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 发表于 2025-3-28 19:35:06
http://reply.papertrans.cn/17/1622/162110/162110_42.png弄污 发表于 2025-3-29 02:42:10
http://reply.papertrans.cn/17/1622/162110/162110_43.png敲竹杠 发表于 2025-3-29 03:52:08
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 发表于 2025-3-29 08:11:01
http://reply.papertrans.cn/17/1622/162110/162110_45.png中子 发表于 2025-3-29 13:32:44
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中世纪 发表于 2025-3-29 18:05:05
http://reply.papertrans.cn/17/1622/162110/162110_47.pngFrequency-Range 发表于 2025-3-29 21:50:57
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 collPatrimony 发表于 2025-3-30 00:40:33
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管理员 发表于 2025-3-30 07:32:15
http://reply.papertrans.cn/17/1622/162110/162110_50.png