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Accurate scoring of syntactic structures such as head-modifier arcs in dependency parsing typically requires rich, high-dimensional feature representations. A small subset of such features is often selected manually. This is problematic when features lack clear linguistic meaning as in embeddings or when the information is blended across features. In this(More)
Recommender systems involve an inherent trade-off between accuracy of recommendations and the extent to which users are willing to release information about their preferences. In this paper, we explore a two-tiered notion of privacy where there is a small set of " public " users who are willing to share their preferences openly, and a large set of " private(More)
Matrix factorization (MF) has evolved as one of the most accurate approaches to collaborative filtering. In this paper, we extend the probabilistic MF framework as to account for multiple observations for each matrix element. This significantly improves the accuracy of recommender systems in several areas: (1) aggregation of ratings concerning items(More)
In this paper, we study the distinguishability of multipartite quantum states by separable operations. We first present a necessary and sufficient condition for a finite set of orthogonal quantum states to be distinguishable by separable operations. An analytical version of this condition is derived for the case of <i>(D</i>-1) pure states, where <i>D</i>(More)
Accounting for missing ratings in available training data was recently shown [3, 17] to lead to large improvements in the top-k hit rate of recommender systems, compared to state-of-the-art approaches optimizing the popular root-mean-square-error (RMSE) on the observed ratings. In this paper, we take a Bayesian approach, which lends itself naturally to(More)
OBJECTIVE Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors(More)
In this paper, we present an improved RRT-based motion planner for autonomous vehicles to effectively navigate in cluttered environments with narrow passages. The planner first presents X-test that can identify passable narrow passages, and then perform an efficient obstacles-based extension operation within passable narrow passages. In order to generate a(More)
Through the analysis of the characteristics of Bluetooth piconet and Bluetooth's security architecture, this paper gives out a scheme of group key agreement based on Diffie-Hellman key agreement protocol. It affords a method that nodes can authenticate each other in the Bluetooth piconet and defeat threats derived from Bluetooth link-level. In the last(More)