Collaborative Filtering via Group-Structured Dictionary Learning
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چکیده
Structured sparse coding and the related structured dictionary learning problems are novel research areas in machine learning. In this paper we present a new application of structured dictionary learning for collaborative filtering based recommender systems. Our extensive numerical experiments demonstrate that the presented method outperforms its state-of-the-art competitors and has several advantages over approaches that do not put structured constraints on the dictionary elements.
منابع مشابه
Appendix Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data
Table 1: Final tuned parameter values for Fugue, BarrieredFugue, GraphLab and PSGD. All the methods are tuned to perform optimally. η0 is the initial step size, where η is defined in equation 4. λ is the Dictionary Learning `1 penalty defined in equation 2. η ′ is parameter that modifies the learning rate when extra updates are executed while waiting for slow workers. step dec is a parameter fo...
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تاریخ انتشار 2012