Accurate value estimates are important for off-policy reinforcement learning. Algorithms based on temporal difference learning typically prone to an over- or underestimation bias building up over time. In this letter, we propose a general method called Adaptively Calibrated Critics (ACC) that uses the most recent high variance but unbiased on-policy rollouts alleviate of low targets. We apply A...

In harmonic radar (HR), the radio frequency transmitter illuminates a nonlinear target (the tag), causing return signal to consist of harmonics at multiples transmitted carrier frequency. Of them, second is usually strongest and one which receiver tuned. This difference distinguishes tag reflection from environmental clutter, remains uplink (transmitter tag) However, passive nature HR tags seve...

In recent years several catastrophic power systems blackouts have occurred worldwide. Various reasons have been declared for these failures. Economical limitations due to power system restructuring restrictions, inadvertent operation of protective relays and inefficient design of conventional load shedding schemes are of the most important reasons causing these blackouts. In fact, due to both e...

We consider the problem of how to best parallelize range queries in a massive scale distributed database. In traditional systems the focus has been on maximizing parallelism, for example by laying out data to achieve the highest throughput. However, in a massive scale database such as our PNUTS system [11] or BigTable [10], maximizing parallelism is not necessarily the best strategy: the system...

Large margin classifiers have been shown to be very useful in many applications. The Support Vector Machine is a canonical example of large margin classifiers. Despite their flexibility and ability in handling high dimensional data, many large margin classifiers have serious drawbacks when the data are noisy, especially when there are outliers in the data. In this paper, we propose a new weight...

In this paper, we present an adaptive approach for simulating elastic deformation of homogeneous and inhomogeneous objects based on continuum mechanics. In typical adaptive simulation approaches, the deforming elastic object is usually subdivided to form a tree structure on the fly. However, they are not directly applicable for inhomogeneous elastic deformation, since the elasticity matrix, whi...

Distance fields are an important volume representation. A high quality distance field facilitates accurate surface characterization and gradient estimation. However, due to Nyquist’s Law, no existing volumetric methods based on the linear sampling theory can fully capture surface details, such as corners and edges, in 3D space. We propose a novel complete distance field representation (CDFR) th...