The paper presents and discusses direct and indirect tuning of a knowledge-driven harmonization model for tonal music. Automatic harmonization is a data analysis problem: an algorithm processes a music notation document and generates specific meta-data (harmonic functions). The proposed model could be seen as an Expert System with manually selected weights, based largely on the music theory. It...

A system separating objects moving within a slow changing background is presented. The originality of the approach resides in two related components. First, the change detection robust to camera noise which does not require any sophisticated parametric tuning as it is based on a probabilistic method. Second, the change is detected between a video frame representing a scene at a given time, and ...

Tone reproduction algorithms attempt to compress a large range of pixel values into a smaller range that is suitable for display on devices with limited dynamic range. A recently proposed tone reproduction operator achieved this goal by emulating photographic practice. Like in photography, the manual tuning of a small set of intuitive parameters was required. In this paper we extend this photog...

We report a series of simulations on the well-known “other-race effect.” We trained an autoassociative network on a majority and a minority race of faces, and tested the model’s ability to process faces from the two races in different ways. First, the model was better able to reconstruct unlearned majority faces than minority faces. Secondly, the average inter-face similarity was higher for the...

The self-tuning PID/I controller (ST-PID-2) with new algorithm of tuning of test signal is proposed. This controller is based on the self-tuning PID/I controller (ST-PID-1) but have better algorithm of tuning of test signal. It is assumed that plant is described by first order with time delay. Coefficients of plant are unknown and can be changed in some isolated time moments. Self-tuning PID/I ...

The paper presents the method of on-line diagnostics of the bed temperature controller for the fluidized bed boiler. Proposed solution is based on the methods of statistical process control. Detected decrease of the bed temperature control quality is used to activate the controller self-tuning procedure. The algorithm that provides optimal tuning of the bed temperature controller is also propos...

A closed loop self-tuning 256kb 6T SRAM with 0.38V-1.2V extended operating range using combined read and write assists and canary-based VMIN tracking is presented. 337X and 4.3X power reductions are achieved using multiple assists and VMIN tracking, respectively; combining both saves 1444X in active power and 12.4X in leakage at the 0.38V. Keywords—self-tuning SRAM; combined assists; canary SRA...

The solution to fine tuning is one of the principal motivations for Beyond the Standard Model (BSM) Studies. However constraints on new physics indicate that many of these BSM models are also fine tuned (although to a much lesser extent). To compare these BSM models it is essential that we have a reliable, quantitative measure of tuning. We review the measures of tuning used in the literature a...

Adaptive Optimization Hyperparameter tuning is a big cost of deep learning. Momentum: a key hyperparameter to SGD and variants. Adaptive methods, e.g. Adam1, don’t tune momentum. YellowFin optimizer • Based on the robustness properties of momentum. • Auto-tuning of momentum and learning rate in SGD. • Closed-loop momentum control for async. training. Experiments ResNet and LSTM YellowFin runs w...

The influence of space charge on emittance growth is studied in simulations of a coasting beam exposed to a strong octupolar perturbation in an otherwise linear lattice, and under stationary parameters. We explore the importance of selfconsistency by comparing results with a non-self-consistent model, where the space charge electric field is kept “frozen-in” to its initial values. For Gaussian ...