Kernel embedding of distributions has led to many recent advances in machine learning. However, latent and low rank structures prevalent in real world distributions have rarely been taken into account in this setting. Furthermore, no prior work in kernel embedding literature has addressed the issue of robust embedding when the latent and low rank information are misspecified. In this paper, we ...

In this paper we prove Vaught's conjecture for superstable theories in which each complete type has nite U? rank. The general idea is to associate with the theory an V ? deenable group G (called the structure group) which controls the isomorphism types of the models. We use module theory to show that when the theory has few countable models and M is a countable model there is a nice decompositi...

Partial) Unit Memory ((P)UM) codes provide a powerful possibility to construct convolutional codes based on block codes in order to achieve a high decoding performance. In this contribution, a construction based on Gabidulin codes is considered. This construction requires a modified rank metric, the so–called sum rank metric. For the sum rank metric, the free rank distance, the extended row ran...

While machine learning methods for named entity recognition (mention-level detection) have become common, machine learning methods have rarely been applied to normalization (concept-level identification). Recent research introduced a machine learning method for normalization based on pairwise learning to rank. This method, DNorm, uses a linear model to score the similarity between mentions and ...

Several compositional distributional semantic methods use tensors to model multi-way interactions between vectors. Unfortunately, the size of the tensors can make their use impractical in large-scale implementations. In this paper, we investigate whether we can match the performance of full tensors with low-rank approximations that use a fraction of the original number of parameters. We investi...

as organization developed and the control area of management increased, assessment and control of organizational units became more essential for managers. usually managers try to assess the performance of units by defining and measuring varied indexes in operational department. also this method transforms some idea to managers, but doesn't attention to interrelationship between these index...

In this work we propose schemes for joint modelorder and step-size adaptation of reduced-rank adaptive filters. The proposed schemes employ reduced-rank adaptive filters in parallel operating with different orders and step sizes, which are exploited by convex combination strategies. The reduced-rank adaptive filters used in the proposed schemes are based on a joint and iterative decimation and ...