Market Efficiency and the NHL totals betting market: Is there an under bias?

Sports betting and racetrack markets continue to be utilized by academic researchers to provide insights into theories relating to more complex speculative markets. Previous investigations have focused on testing the efficient markets hypotheses and behavioral biases of the participants. This paper investigates the market efficiency of the National Hockey League (NHL) goal totals over/under betting market. The market is found to be inefficient and simple wagering strategies are identified that result in profitable returns.market efficiency, under bias, National Hockey League, sports betting markets, goal totals

Frames and applications : distribution of frame coeficients, integer frames and phase retrieval

The present dissertation is divided into two main areas: frame theoretic results and applications of frames. In particular, the beginning half develops the first detailed theory of the distribution of frame coefficients. Next, the first systematic study of integer frames is included. The latter half of the dissertation is concerned with the application of frames to the area of signal reconstruction. In particular, phase retrieval by subspaces components and norm retrieval are discussed

I-vector estimation using informative priors for adaptation of deep neural networks

This is the author accepted manuscript. The final version is available from ISCA via http://www.isca-speech.org/archive/interspeech_2015/i15_2872.html Supporting data for this paper is available at the http://www.repository.cam.ac.uk/handle/1810/248387 data repository.I-vectors are a well-known low-dimensional representation of speaker space and are becoming increasingly popular in adaptation of state-of-the-art deep neural network (DNN) acoustic models. One advantage of i-vectors is that they can be used with very little data, for example a single utterance. However, to improve robustness of the i-vector estimates with limited data, a prior is often used. Traditionally, a standard normal prior is applied to i-vectors, which is nevertheless not well suited to the increased variability of short utterances. This paper proposes a more informative prior, derived from the training data. As well as aiming to reduce the non-Gaussian behaviour of the i-vector space, it allows prior information at different levels, for example gender, to be used. Experiments on a US English Broadcast News (BN) transcription task for speaker and utterance i-vector adaptation show that more informative priors reduce the sensitivity to the quantity of data used to estimate the i-vector. The best configuration for this task was utterance-level test i-vectors enhanced with informative priors which gave a 13% relative reduction in word error rate over the baseline (no i-vectors) and a 5% over utterance-level test i-vectors with standard prior.This work was supported by EPSRC Programme Grant EP/I031022/1 (Natural Speech Technology)

Spreading of Latex Particles on a Substrate

We have investigated both experimentally and theoretically the spreading behavior of latex particles deposited on solid substrates. These particles, which are composed of cross-linked polymer chains, have an intrinsic elastic modulus. We show that the elasticity must be considered to account for the observed contact angle between the particle and the solid substrate, as measured through atomic force microscopy techniques. In particular, the work of adhesion computed within our model can be significantly larger than that from the classical Dupr\'{e} formula.Comment: 7 pages, 7 figures, to appear in Europhys. Let