A matrix CFT at multiple large charges

We investigate matrix models in three dimensions where the global $\text{SU}(N)$ symmetry acts via the adjoint map. Analyzing their ground state which is homogeneous in space and can carry either a unique or multiple fixed charges, we show the existence of at least two distinct fixed points of the renormalization group (RG) flow. In particular, the one type of those fixed points manifests itself via tractable deviations in the large-charge expansion from the known predictions in the literature. We demonstrate most of the novel features using mainly the example of the $\text{SU}(4)$ matrix theory to compute the anomalous dimension of the lowest scalar operator with large global charge(s).Comment: 1+36 pages, 2 figures, minor clarifications added, version to be published in JHE

Surgical Phase Recognition of Short Video Shots Based on Temporal Modeling of Deep Features

Recognizing the phases of a laparoscopic surgery (LS) operation form its video constitutes a fundamental step for efficient content representation, indexing and retrieval in surgical video databases. In the literature, most techniques focus on phase segmentation of the entire LS video using hand-crafted visual features, instrument usage signals, and recently convolutional neural networks (CNNs). In this paper we address the problem of phase recognition of short video shots (10s) of the operation, without utilizing information about the preceding/forthcoming video frames, their phase labels or the instruments used. We investigate four state-of-the-art CNN architectures (Alexnet, VGG19, GoogleNet, and ResNet101), for feature extraction via transfer learning. Visual saliency was employed for selecting the most informative region of the image as input to the CNN. Video shot representation was based on two temporal pooling mechanisms. Most importantly, we investigate the role of 'elapsed time' (from the beginning of the operation), and we show that inclusion of this feature can increase performance dramatically (69% vs. 75% mean accuracy). Finally, a long short-term memory (LSTM) network was trained for video shot classification based on the fusion of CNN features with 'elapsed time', increasing the accuracy to 86%. Our results highlight the prominent role of visual saliency, long-range temporal recursion and 'elapsed time' (a feature so far ignored), for surgical phase recognition.Comment: 6 pages, 4 figures, 6 table

Public beliefs and corruption in a repeated psychological game

This paper investigates the role of guilt aversion for corruption in public administration. Corruption is modeled as the outcome of a game played between a bureaucrat, a lobby, and the public. There is a moral cost of corruption for the bureaucrat, who is averse to letting the public down. We study how the behavior of the lobby and the bureaucrat depend on perceived public beliefs, when these are constant and when they are allowed to vary over time. With time-varying beliefs, corruption is more likely when the horizon of the game is relatively long and when public beliefs are initially low and are updated fast.psychological games, corruption, bureaucracy, guilt, third party

Spectrally approximating large graphs with smaller graphs

How does coarsening affect the spectrum of a general graph? We provide conditions such that the principal eigenvalues and eigenspaces of a coarsened and original graph Laplacian matrices are close. The achieved approximation is shown to depend on standard graph-theoretic properties, such as the degree and eigenvalue distributions, as well as on the ratio between the coarsened and actual graph sizes. Our results carry implications for learning methods that utilize coarsening. For the particular case of spectral clustering, they imply that coarse eigenvectors can be used to derive good quality assignments even without refinement---this phenomenon was previously observed, but lacked formal justification.Comment: 22 pages, 10 figure

Corporate governance in Greece: developments and policy implications

The upgrading of the Greek capital market and the effort to join other mature capital markets has posed corporate governance reform as a first priority. In addition, the 2004 Olympic Games put the Greek market in the international spotlight and will likely invite interest from foreign investors. More than ever, an efficient corporate governance framework is condition sine qua non for the competitive transformation of the capital market and the business world. At the same time the European Union (EU) faces both the pressure and challenge for harmonization of the laws and regulations and convergence of corporate governance systems, especially after the entrance of the new member states. The paper has two objectives: (i) to present the main aspects of corporate governance in Greece, contributing to the relevant growing body of literature, and (ii) to place the current corporate governance developments and trends in Greece within the international debate, especially in the light of the recent debate to improve and convergence corporate governance in EU. Firstly, I review the corporate governance debate and its implication at the EU level. Secondly, I describe the corporate governance framework in Greece in the light of the recent key reforms. Finally, I summarize the overall findings and proceed with some critical points and recommendations for the potential future direction of the corporate governance agenda in Greece.Corporate governance, rating, disclosure, ownership, Greece