Continuous time systems identification with unknown noise covariance = Systèmes d'identification de temps continu avec co-variation de bruit (ou bruits) inconnus = Identifikation zeitkontinuierlicher systeme mit unbekannter rauschkovarianz

In identifying parameters of a continuous-time dynamical system, a difficulty arises when the observation noise covariance is unknown. The present paper solves this problem in the case of a linear time-invariant system with white noise affecting additively both the state and the observation. The problem is that the likelihood functional cannot be obtained when the observation noise covariance is unknown. A related procedure is suggested, however, and the estimates are obtained by finding roots of an appropriate functional. It is shown that the estimates obtained are consistent

Prefrontal involvement in imitation learning of hand actions : effects of practice and expertise.

In this event-related fMRI study, we demonstrate the effects of a single session of practising configural hand actions (guitar chords) on cortical activations during observation, motor preparation, and imitative execution. During the observation of non-practised actions, the mirror neuron system (MNS), consisting of inferior parietal and ventral premotor areas, was more strongly activated than for the practised actions. This finding indicates a strong role of the MNS in the early stages of imitation learning. In addition, the dorsolateral prefrontal cortex (DLPFC) was selectively involved during observation and motor preparation of the non-practised chords. This finding confirms Buccino et al.’s (2004a) model of imitation learning: for actions that are not yet part of the observer’s motor repertoire, DLPFC engages in operations of selection and combination of existing, elementary representations in the MNS. The pattern of prefrontal activations further supports Shallice’s (2004) proposal of a dominant role of the left DLPFC in modulating lower-level systems, and of a dominant role of the right DLPFC in monitoring operations

On Identifying a Massive Number of Distributions

Finding the underlying probability distributions of a set of observed sequences under the constraint that each sequence is generated i.i.d by a distinct distribution is considered. The number of distributions, and hence the number of observed sequences, are let to grow with the observation blocklength $n$. Asymptotically matching upper and lower bounds on the probability of error are derived.Comment: Under Submissio

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions. Bayesian optimization employs the Bayesian technique of setting a prior over the objective function and combining it with evidence to get a posterior function. This permits a utility-based selection of the next observation to make on the objective function, which must take into account both exploration (sampling from areas of high uncertainty) and exploitation (sampling areas likely to offer improvement over the current best observation). We also present two detailed extensions of Bayesian optimization, with experiments---active user modelling with preferences, and hierarchical reinforcement learning---and a discussion of the pros and cons of Bayesian optimization based on our experiences

Particle streak velocity field measurements in a two-dimensional mixing layer

Using digital image processing of particle streak photography, the streamwise and perpendicular components of the velocity field were investigated, in the mid‐span plane of a two‐dimensional mixing layer, with a 6:1 velocity ratio. The Reynolds number of the flow, based on the local vorticity thickness and the velocity difference across the layer, ranged from 1360 to 2520, in the plane of observation. The significant result of this experiment was that the region of vorticity bearing fluid is confined to a small fraction of the flow. A second finding, consistent with the small regions of concentrated vorticity, was the observation of instantaneous streamwise velocity reversal, in the laboratory frame, in small regions of the flow

Phase separation in doped Mott insulators

Motivated by the commonplace observation of Mott insulators away from integer filling, we construct a simple thermodynamic argument for phase separation in first-order doping-driven Mott transitions. We show how to compute the critical dopings required to drive the Mott transition using electronic structure calculations for the titanate family of perovskites, finding good agreement with experiment. The theory predicts the transition is percolative and should exhibit Coulomb frustration.Comment: Updated acknowledgement

Abduction and Dialogical Proof in Argumentation and Logic Programming

We develop a model of abduction in abstract argumentation, where changes to an argumentation framework act as hypotheses to explain the support of an observation. We present dialogical proof theories for the main decision problems (i.e., finding hypothe- ses that explain skeptical/credulous support) and we show that our model can be instantiated on the basis of abductive logic programs.Comment: Appears in the Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014