Offline to Online Conversion

We consider the problem of converting offline estimators into an online predictor or estimator with small extra regret. Formally this is the problem of merging a collection of probability measures over strings of length 1,2,3,... into a single probability measure over infinite sequences. We describe various approaches and their pros and cons on various examples. As a side-result we give an elementary non-heuristic purely combinatoric derivation of Turing's famous estimator. Our main technical contribution is to determine the computational complexity of online estimators with good guarantees in general.Comment: 20 LaTeX page

Thermal effects on CH3_3NH3_3PbI3_3 perovskite from ab-initio molecular dynamics simulations

We present a molecular dynamics simulation study of CH$_3$NH$_3$PbI$_3$ based on forces calculated from density functional theory. The simulation were performed on model systems having 8 and 27 unit cells, and for a total simulation time of 40 ps in each case. Analysis of the finite size effects, in particular the mobility of the organic component, suggests that the smaller system is over correlated through the long range electrostatic interaction. In the larger system this finite size artifact is relaxed producing a more reliable description of the anisotropic rotational behavior of the methyl ammonium molecules. The thermal effects on the optical properties of the system were also analyzed. The HOMO-LUMO energy gap fluctuates around its central value with a standard deviation of approximately 0.1 eV. The projected density of states consistently place the Fermi level on the $p$ orbitals of the I atoms, and the lowest virtual state on $p$ orbitals of the Pb atoms throughout the whole simulation trajectory.Comment: 16 pages, 11 figure

MDL Convergence Speed for Bernoulli Sequences

The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total expected square loss is a particularly interesting performance measure: (a) this quantity is finitely bounded, implying convergence with probability one, and (b) it additionally specifies the convergence speed. For MDL, in general one can only have loss bounds which are finite but exponentially larger than those for Bayes mixtures. We show that this is even the case if the model class contains only Bernoulli distributions. We derive a new upper bound on the prediction error for countable Bernoulli classes. This implies a small bound (comparable to the one for Bayes mixtures) for certain important model classes. We discuss the application to Machine Learning tasks such as classification and hypothesis testing, and generalization to countable classes of i.i.d. models.Comment: 28 page

Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces

In practical Bayesian optimization, we must often search over structures with differing numbers of parameters. For instance, we may wish to search over neural network architectures with an unknown number of layers. To relate performance data gathered for different architectures, we define a new kernel for conditional parameter spaces that explicitly includes information about which parameters are relevant in a given structure. We show that this kernel improves model quality and Bayesian optimization results over several simpler baseline kernels.Comment: 6 pages, 3 figures. Appeared in the NIPS 2013 workshop on Bayesian optimizatio

Nucleate pool boiling investigation on a silicon test section with micro-fabricated cavities

The basic mechanisms of nucleate boiling are still not completely understood, in spite of the many numerical and experimental studies dedicated to the topic. The use of a hybrid code allows reasonable computational times for simulations of a solid plate with a large population of artificial micro-cavities with fixed distribution. This paper analyses the guidelines for the design, through numerical simulations, of the location and sizes of micro-fabricated cavities on a new silicon test section immersed in FC-72 at the saturation temperature for different pressures with an imposed heat flux applied at the back of the plate. Particular focus is on variations of wall temperature around nucleation sites

Tunable coupling of qubits: nonadiabatic corrections

We analyze the coupling of qubits mediated by a tunable and fast element beyond the adiabatic approximation. The nonadiabatic corrections are important and even dominant in parts of the relevant parameter range. As an example, we consider the tunable capacitive coupling between two charge qubits mediated by a gated Josephson junction, as suggested by Averin and Bruder. The nonadiabatic, inductive contribution persists when the capacitive coupling is tuned to zero. On the other hand, the total coupling can be turned off (in the rotating wave approximation) if the qubits are operated at symmetry points.Comment: 7 pages, 2 figures, accepted in Europhysics Letter

Role of protein kinase C in inhibition of renin release caused by vasoconstrictors

It was the aim of the present study to get insight into some of the intracellular mechanisms by which the vasoconstrictor hormones angiotensin II (ANG II), arginine vasopressin (AVP), and norepinephrine (NE) inhibit renin release from renal juxtaglomerular cells. To this end a primary cell culture from rat renal cortex was established that consisted of 50% juxtaglomerular cells. The cultured juxtaglomerular cells contained prominent renin granules closely resembling those in the intact kidney and responded to a number of stimuli of renin release. By using these cultures, we found that ANG II (10(-7) M), AVP (10(-6) M), and NE (10(-5) M) inhibited renin release and increased the calcium permeability of the plasma membrane of the cultured cells. Both the effects on renin release and on calcium permeability could be diminished or even be abolished by the calcium channel blocker verapamil (Vp) (10(-5) M). ANG II, AVP, and NE led to an increased formation of diacylglycerol (DAG), a well-known stimulator of protein kinase C (PKC). Moreover, a direct stimulation of PKC by 12-O-tetradecanoylphorbol-13-acetate (TPA) (10(-8)-10(-6) M) also inhibited renin release and increased the calcium permeability of the cell membrane. Similar to ANG II, AVP, and NE, the effects of TPA on calcium permeability and renin release could be diminished by Vp. In conclusion, these results point toward a common mechanism by which vasoconstrictors inhibit renin release from renal juxtaglomerular cells: ANG II, AVP, and NE activate a phospholipase C, which generates DAG.(ABSTRACT TRUNCATED AT 250 WORDS