http://hdl.handle.net/1721.1/5458 Sat, 18 May 2013 13:50:54 GMT 2013-05-18T13:50:54Z http://hdl.handle.net/1721.1/78590 High Spatial Resolution BRDFs with Metallic powders Using Wave Optics Analysis Levin, Anat; Glasner, Daniel; Xiong, Ying; Durand, Fredo; Freeman, William; Matusik, Wojciech; Zickler, Todd This manuscript completes the analysis of our SIGGRAPH 2013 paper "Fabricating BRDFs at High Spatial Resolution Using Wave Optics" in which photolithography fabrication was used for manipulating reflectance effects. While photolithography allows for precise reflectance control, it is costly to fabricate. Here we explore an inexpensive alternative to micro-fabrication, in the form of metallic powders. Such powders are readily available at a variety of particle sizes and morphologies. Using an analysis similar to the micro-fabrication paper, we provide guidelines for the relation between the particles' shape and size and the reflectance functions they can produce. Wed, 24 Apr 2013 04:00:00 GMT http://hdl.handle.net/1721.1/78590 2013-04-24T04:00:00Z http://hdl.handle.net/1721.1/78573 Compositional Policy Priors Wingate, David; Diuk, Carlos; O'Donnell, Timothy; Tenenbaum, Joshua; Gershman, Samuel This paper describes a probabilistic framework for incorporating structured inductive biases into reinforcement learning. These inductive biases arise from policy priors, probability distributions over optimal policies. Borrowing recent ideas from computational linguistics and Bayesian nonparametrics, we define several families of policy priors that express compositional, abstract structure in a domain. Compositionality is expressed using probabilistic context-free grammars, enabling a compact representation of hierarchically organized sub-tasks. Useful sequences of sub-tasks can be cached and reused by extending the grammars nonparametrically using Fragment Grammars. We present Monte Carlo methods for performing inference, and show how structured policy priors lead to substantially faster learning in complex domains compared to methods without inductive biases. Fri, 12 Apr 2013 04:00:00 GMT http://hdl.handle.net/1721.1/78573 2013-04-12T04:00:00Z http://hdl.handle.net/1721.1/78359 Task-Structured Probabilistic I/O Automata Canetti, Ran; Cheung, Ling; Kaynar, Dilsun; Liskov, Moses; Lynch, Nancy; Pereira, Olivier; Segala, Roberto Modeling frameworks such as Probabilistic I/O Automata (PIOA) and Markov Decision Processes permit both probabilistic and nondeterministic choices. In order to use these frameworks to express claims about probabilities of events, one needs mechanisms for resolving nondeterministic choices. For PIOAs, nondeterministic choices have traditionally been resolved by schedulers that have perfect information about the past execution. However, these schedulers are too powerful for certain settings, such as cryptographic protocol analysis, where information must sometimes be hidden. Here, we propose a new, less powerful nondeterminism-resolution mechanism for PIOAs, consisting of tasks and local schedulers. Tasks are equivalence classes of system actions that are scheduled by oblivious, global task sequences. Local schedulers resolve nondeterminism within system components, based on local information only. The resulting task-PIOA framework yields simple notions of external behavior and implementation, and supports simple compositionality results. We also define a new kind of simulation relation, and show it to be sound for proving implementation. We illustrate the potential of the task-PIOAframework by outlining its use in verifying an Oblivious Transfer protocol. http://hdl.handle.net/1721.1/78359 http://hdl.handle.net/1721.1/78248 Tracking 3-D Rotations with the Quaternion Bingham Filter Glover, Jared; Kaelbling, Leslie Pack A deterministic method for sequential estimation of 3-D rotations is presented. The Bingham distribution is used to represent uncertainty directly on the unit quaternion hypersphere. Quaternions avoid the degeneracies of other 3-D orientation representations, while the Bingham distribution allows tracking of large-error (high-entropy) rotational distributions. Experimental comparison to a leading EKF-based filtering approach on both synthetic signals and a ball-tracking dataset shows that the Quaternion Bingham Filter (QBF) has lower tracking error than the EKF, particularly when the state is highly dynamic. We present two versions of the QBF, suitable for tracking the state of first- and second-order rotating dynamical systems. Wed, 27 Mar 2013 04:00:00 GMT http://hdl.handle.net/1721.1/78248 2013-03-27T04:00:00Z