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In the field of recommender systems, the Beer & Nappies is a famous story, which reveals the latent relationships between different categories of items. Though matrix factorization (MF) has demonstrated its great effectiveness in most previous work, it neglects the co-occurrences of items selected by individuals. In most MF-based models, the latent preferences of users (or the latent categories...
Exemplar-based clustering has drawn much attention in recent years as it produces state-of-the-art results on many practical clustering problems. However, spatial information is missed in the exemplar-based clustering methods, resulting in difficulties in some applications, for example in the image segmentation problem. In this paper, we investigate the issue of integrating spatial information into...
Data collection is a fundamental issue in wireless sensor networks. In many application scenarios for sensor networks, approximate data collection is a wise choice due to the constraints in communication bandwidth and energy budget. In this paper, we focus on efficient approximate data collection with given error bounds in wireless sensor networks. The key idea of our data collection approach ADC...
In this paper, we address the optimal power allocation problem for minimizing the notion of information theoretic outage for an M parallel block-Rayleigh-fading channels using a finite rate power codebook (limited feedback). In contrast to the existing literature on outage minimization for MIMO systems with limited feedback, we derive effective approximations to the channel quantization regions in...
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