Universality of Bayesian Predictions

Given the sequential update nature of Bayes rule, Bayesian methods find natural application to prediction problems. Advances in computational methods allow to routinely use Bayesian methods in econometrics. Hence, there is a strong case for feasible predictions in a Bayesian framework. This paper studies the theoretical properties of Bayesian predictions and shows that under minimal conditions we can derive finite sample bounds for the loss incurred using Bayesian predictions under the Kullback-Leibler divergence. In particular, the concept of universality of predictions is discussed and universality is established for Bayesian predictions in a variety of settings. These include predictions under almost arbitrary loss functions, model averaging, predictions in a non stationary environment and under model miss-specification. Given the possibility of regime switches and multiple breaks in economic series, as well as the need to choose among different forecasting models, which may inevitably be miss-specified, the finite sample results derived here are of interest to economic and financial forecasting

Comment on the European Parliament Draft Report on the proposal for a recovery and resolution directive : (Rapporteur: Gunnar Hökmark) – Doc 2012/0150 (COD) of 11 October 2012 –

This present comment suggests an amendment to the proposal for a directive of the European Parliament and of the Council, establishing a framework for the recovery and resolution of credit institutions and investment firms. The current proposal focuses on bail-in, but does not sufficiently take into account the pressure exerted on central bankers, supervisors and politicians by the fear of interbank contagion. The only way out of this hold-up type of situation can be found in bail-in bonds. Bail-in bonds are dedicated loss taking debt instruments, whose status of being first in line if it comes to default is clearly communicated from day one

New Combinatorial Construction Techniques for Low-Density Parity-Check Codes and Systematic Repeat-Accumulate Codes

This paper presents several new construction techniques for low-density parity-check (LDPC) and systematic repeat-accumulate (RA) codes. Based on specific classes of combinatorial designs, the improved code design focuses on high-rate structured codes with constant column weights 3 and higher. The proposed codes are efficiently encodable and exhibit good structural properties. Experimental results on decoding performance with the sum-product algorithm show that the novel codes offer substantial practical application potential, for instance, in high-speed applications in magnetic recording and optical communications channels.Comment: 10 pages; to appear in "IEEE Transactions on Communications

A methodology for determining the resolvability of multiple vehicle occlusion in a monocular traffic image sequence

This paper proposed a knowledge-based methodology for determining the resolvability of N occluded vehicles seen in a monocular image sequence. The resolvability of each vehicle is determined by: firstly, deriving the relationship between the camera position and the number of vertices of a projected cuboid on the image; secondly, finding the direction of the edges of the projected cuboid in the image; and thirdly, modeling the maximum number of occluded cuboid edges of which the occluded cuboid is irresolvable. The proposed methodology has been tested rigorously on a number of real world monocular traffic image sequences that involves multiple vehicle occlusions, and is found to be able to successfully determine the number of occluded vehicles as well as the resolvability of each vehicle. We believe the proposed methodology will form the foundation for a more accurate traffic flow estimation and recognition system.published_or_final_versio

Strong Coordination over Multi-hop Line Networks

We analyze the problem of strong coordination over a multi-hop line network in which the node initiating the coordination is a terminal network node. We assume that each node has access to a certain amount of randomness that is local to the node, and that the nodes share some common randomness, which are used together with explicit hop-by-hop communication to achieve strong coordination. We derive the trade-offs among the required rates of communication on the network links, the rates of local randomness available to network nodes, and the rate of common randomness to realize strong coordination. We present an achievable coding scheme built using multiple layers of channel resolvability codes, and establish several settings in which this scheme is proven to offer the best possible trade-offs.Comment: 35 pages, 9 Figures, 4 Tables. A part of this work were published in the 2015 IEEE Information Theory Workshop, and a part was accepted for publication in the 50th Annual Conference on Information Sciences and System

The Bing-Borsuk and the Busemann Conjectures

We present two classical conjectures concerning the characterization of manifolds: the Bing Borsuk Conjecture asserts that every $n$-dimensional homogeneous ANR is a topological $n$-manifold, whereas the Busemann Conjecture asserts that every $n$-dimensional $G$-space is a topological $n$-manifold. The key object in both cases are so-called {\it generalized manifolds}, i.e. ENR homology manifolds. We look at the history, from the early beginnings to the present day. We also list several open problems and related conjectures.Comment: We have corrected three small typos on pages 8 and