Music has been shown to impact the affective states of the listener. The emotion in music task at the MediaEval challenge 2015 focuses on predicting the affective dimensions of valence and arousal in music using low level features. In particular, this edition of the challenge involves prediction on full length songs given a training set containing smaller 30 second clips. We approach the proble...

Recent advances in the measurement of volatility have utilized high frequency intraday data to produce what are generally known as realised volatility estimates. It has been shown that forecasts generated from such estimates are of positive economic value in the context of portfolio allocation. This paper considers the link between the value of such forecasts and the loss function under which m...

あらまし 音素セグメンテーションは,音声認識や音声合成における基本的な問題である。しかしながら,言語情報 や音響モデルに関する知識を全く用いない教師なし音素セグメンテーションは,非常に難解な問題として挙げられる。 その本質的問題は「どうのように最適な分割を定義する か」である。本論文では,最適な分割を確率的な枠組みで定 式化する。統計分析と情報理論を用いて、最適化対象として三つの目標関数を提案する:Mean Square Error (MSE), Log Determinant (LD) and Rate Distortion (RD)。特に RD関数は、情報レート歪み理論に基づいて定義されてお り、人間の言語知覚メカニズムと関連性を見いだすことができる。さらに,RD関数を用いて,最適な分割が直交変換 に対して不変性をもつことを証明した。また,提案された目的関数を最適化するため、時間...

In this paper, a regression type estimator representing a class of estimators is proposed to estimate the population mean of the study variable. The bias and mean square error of the proposed estimator are obtained. Also the optimizing value of the unknown parameter is derived and the expression of minimum mean square error is obtained. Further since the proposed estimator is biased, a jackknif...

Learning Factors Analysis (LFA), a form of student modeling, is used to predict whether a student can correctly answer a tutor question. Existing evaluations of LFA rely on metrics like the crossvalidated root mean squared error (RMSE). However, the LFA output can be a binary classification (the student will be correct or not), so we can use classification metrics, such as precision and recall,...

This paper develops a forecasting model for important macroeconomic variables in the state of Indiana. In this study, we specify a Bayesian Vector Autoregression (BVAR) model with Litterman’s prior. A comparison with the Vector Autoregression (VAR) model shows that BVAR improves forecast by reducing root mean square

The finite sample properties of the Fourier estimator of integrated volatility under market microstructure noise are studied. Analytic expressions for the bias and the mean squared error of the contaminated estimator are derived. These formulae can be practically used to design optimal MSE-based estimators, which are very robust and efficient in the presence of noise. Moreover an empirical anal...

This paper investigates whether using natural logarithms (logs) of price indices for forecasting inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation rates for a number of European countries and the USA based on monthly seasonal consumer price indices are considered. Stochastic seasonality and deterministic seasonality models are used. In man...

Fluoroscopy is currently used in treatment planning for patients undergoing radiation therapy. Radiation oncologists would like to maximize the amount of dose the tumor receives and minimize the amount delivered to the surrounding tissues. During treatment, patients breathe freely and so the tumor location will not be fixed. This makes calculating the amount of dose delivered to the tumor, and ...

Validating or accessing the accuracy of soft classification maps has rapidly developed over the past few years. This assessment employs a soft error matrix as generalized from the traditional, hard classification error matrix. However, the impact of positional error on the soft classification is uncertain and whether the well-accepted half-pixel registration accuracy is suitable for the soft cl...