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Titlebook: Neural Information Processing; 20th International C Minho Lee,Akira Hirose,Rhee Man Kil Conference proceedings 2013 Springer-Verlag Berlin

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Multi-regularization for Fuzzy Co-clustering, real world data, there is a strong need to provide an overlapped co-clustering algorithm that mitigates the effect of noise and non-discriminative information, generalizes well to the unseen data, and performs well with respect to several quality measures. In this paper, we introduce a novel fuzzy
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Improvement of the Relaxation Procedure in Concurrent Q-Learning, learning and propose the modification of the relaxation procedure in CQL. We apply the proposed algorithm to the problem of maze in reinforcement learning and validate what kind of behavior the original CQL and the proposed algorithm show for the changes of environment such as the change of goals a
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Modularity Embedding,a low-dimensional depiction of graphs while preserving certain properties of the data. In this manuscript we propose a novel graph embedding method which tries to optimize the “modularity” of graphs during dimensionality reduction. The embedding method has a simple formulation and is naturally relax
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Flexible Nonparametric Kernel Learning with Different Loss Functions,P). In recent years, a number of dedicated solvers have been proposed. Though much better than off-the-shelf SDP solvers, they still cannot scale to large data sets. In this paper, we propose a novel solver based on the alternating direction method of multipliers (ADMM). The key idea is to use a low
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