990041
Arbitrage pricing theory-based Gaussian temporal factor analysis for adaptive portfolio management
Ever since the inception of Markowitz's modern portfolio theory, static portfolio optimization techniques were gradually phased out by dynamic portfolio management due to the growth of popularity in automated trading. In view of the intensive computational needs, it is common to use machine learning approaches on Sharpe ratio maximization for implementing dynamic portfolio optimization. In the literature, return-based approaches which directly used security prices or returns to control portfolio weights were often used. Inspired by the arbitrage pricing theory (APT), some other efforts concentrate on indirect modelling using hidden factors. On the other hand, with regard to the proper risk measure in the Sharpe ratio, downside risk was considered a better substitute for variance. In this paper, we investigate how the Gaussian temporal factor analysis (TFA) technique can be used for portfolio optimization. Since TFA is based on the classical APT model and has the benefit of removing rotation indeterminacy via temporal modelling, using TFA for portfolio management allows portfolio weights to be indirectly controlled by several hidden factors. Moreover, we extend the approach to some other variants tailored for investors according to their investment objectives and degree of risk tolerance.
11164646
Strip line detection and thinning by RPCL-based local PCA
We solve the tasks of strip line detection and thinning in image processing and pattern recognition with the help of a statistical learning technique called rival penalized competitive learning based local principal component analysis. Due to its model selection and noise resistance ability, the technique is experimentally shown to outperform conventional Hough transform and thinning algorithms.
37879675
A new curve detection method: Randomized Hough transform (RHT)
Abstract A new method is proposed for curve detection. For a curve with n parameters, instead of transforming one pixel into a hypersurface of the n -D parameter space as the HT and its variants do, we randomly pick n pixels and map them into one point in the parameter space. In comparison with the HT and its variants, our new method has the advantages of small storage, high speed, infinite parameter space and arbitrarily high resolution. The preliminary experiments have shown that the new method is quite effective.
15052539
A Further Result on the ICA One-Bit-Matching Conjecture
The one-bit-matching conjecture for independent component analysis (ICA) has been widely believed in the ICA community. Theoretically, it has been proved that under the assumption of zero skewness for the model probability density functions, the global maximum of a cost function derived from the typical objective function on the ICA problem with the one-bit-matching condition corresponds to a feasible solution of the ICA problem. In this note, we further prove that all the local maximums of the cost function correspond to the feasible solutions of the ICA problem in the two-source case under the same assumption. That is, as long as the one-bit-matching condition is satisfied, the two-source ICA problem can be successfully solved using any local descent algorithm of the typical objective function with the assumption of zero skewness for all the model probability density functions.
6958967
Dual multivariate auto-regressive modeling in state space for temporal signal separation
Many existing independent component analysis (ICA) approaches result in deteriorated performance in temporal source separation because they have not taken into consideration of the underlying temporal structure of sources. In this paper, we model temporal sources as a general multivariate auto-regressive (AR) process whereby an underlying multivariate AR process in observation space is obtained. In this dual AR modeling, the mixing process from temporal sources to observations is the same as the mixture from the nontemporal residuals of the source AR (SAR) process to that of the observation AR (OAR) process. We can therefore avoid the source temporal effects in performing ICA by learning the demixing system on the independently distributed OAR residuals rather than the time-correlated observations. Particularly, we implement this approach by modeling each source signal as a finite mixture of generalized autoregressive conditional heteroskedastic (GARCH) process. The adaptive algorithms are proposed to extract the OAR residuals appropriately online, together with learning the demixing system via a nontemporal ICA algorithm. The experiments have shown its superior performance on temporal source separation.
16709558
One-Bit-Matching Conjecture for Independent Component Analysis
The one-bit-matching conjecture for independent component analysis (ICA) could be understood from different perspectives but is basically stated as all the sources can be separated as long as there is a one-toone same-sign-correspondence between the kurtosis signs of all source probability density functions (pdf's) and the kurtosis signs of all model pdf's (Xu, Cheung, & Amari, 1998a). This conjecture has been widely believed in the ICA community and implicitly supported by many ICA studies, such as the Extended Infomax (Lee, Girolami, & Sejnowski, 1999) and the soft switching algorithm (Welling & Weber, 2001). However, there is no mathematical proof to confirm the conjecture theoretically. In this article, only skewness and kurtosis are considered, and such a mathematical proof is given under the assumption that the skewness of the model densities vanishes. Moreover, empirical experiments are demonstrated on the robustness of the conjecture as the vanishing skewness assumption breaks. As a by-product, we also show that the kurtosis maximization criterion (Moreau & Macchi, 1996) is actually a special case of the minimum mutual information criterion for ICA.
3234740
Stochastic Ordering for Internet Congestion Control and its Applications
Window growth function for congestion control is a strong determinant of protocol behaviors, especially its second and higher-order behaviors associated with the distribution of transmission rates, its variances, and protocol stability. This paper presents a new stochastic tool, called convex ordering, that provides an ordering of any convex function of transmission rates of two protocols and valuable insights into high order behaviors of protocols. As the ordering determined by this tool is consistent with any convex function of rates, it can be applied to any unknown metric for protocol performance that consists of some high-order moments of transmission rates, as well as those already known such as rate variance. Using the tool, it is analyzed that a protocol with a growth function that starts off with a concave function and then switches to a convex function (e.g., an odd order function such as x3 and x5) around the maximum window size in the previous loss epoch, gives the smallest rate variation under a variety of network conditions. Among existing protocols, BIC and CUBIC have this window growth function. Experimental and simulation results confirm the analytical findings.
303543
Limitations of Equation-Based Congestion Control
We study limitations of an equation-based congestion control protocol, called TCP-friendly rate control (TFRC). It examines how the three main factors that determine TFRC throughput, namely, the TCP-friendly equation, loss event rate estimation, and delay estimation, can influence the long-term throughput imbalance between TFRC and TCP. Especially, we show that different sending rates of competing flows cause these flows to experience different loss event rates. There are several fundamental reasons why TFRC and TCP flows have different average sending rates, from the first place. Earlier work shows that the convexity of the TCP-friendly equation used in TFRC causes the sending rate difference. We report two additional reasons in this paper: 1) the convexity of where is a loss event period and 2) different retransmission timeout period (RTO) estimations of TCP and TFRC. These factors can be the reasons for TCP and TFRC to experience initially different sending rates. But we find that the loss event rate difference due to the differing sending rates greatly amplifies the initial throughput difference; in some extreme cases, TFRC uses around 20 times more, or sometimes 10 times less, bandwidth than TCP. Despite these factors influencing the throughput difference, we also find that simple heuristics can greatly mitigate the problem.
8691766
Media Streaming via TFRC: An Analytical Study of the Impact of TFRC on User-Perceived Media Quality
TCP-Friendly Rate Control (TFRC) is being adopted in Internet standards for congestion control of various streaming media applications. In this paper, we consider the transmission of pre-recorded media from a server to a client by using TFRC, and analytically study the impact of TFRC on user-perceived media quality, which is roughly measured by calculating the rebuffering probability. A rebuffering probability is defined to be the probability that the total duration of all rebuffering events experienced by a user is longer than a certain threshold. Two approaches are presented to help an application determine an appropriate initial buffering delay and media playback rate in order to achieve a certain rebuffering probability under a given network condition. First, we derive a closed- form expression to approximate the average TFRC sending rate, which could be used as the maximum allowed playback rate of a media stream. Second, we develop a queueing model for a TFRC client buffer with the traffic described by a Markov-Renewal- Modulated Deterministic Process (MRMDP), and present an iterative method to calculate the rebuffering probability.
31040454
Determining optimum edible films for kiwifruits using an analytical hierarchy process
Fresh fruits undergo vigorous biological reaction after harvest and their respiration accelerates the natural loss of fruit tissue. Therefore, fruits tend to lose water at room temperature, change appearance, texture, and quality, and thus reduce their commercial value. Kiwifruits rot faster than other fruits due to their high ethylene concentration in atmosphere and their sensitivity to ethylene. Coating fruits with an edible film is an effective storage method at room temperature. In this paper, mathematical models of the permeability of edible films and the analytic hierarchy process model are used to determine the optimum edible film for preserving kiwifruits.
34666787
Applying Agent into Web Testing and Evolution
Automatic Web testing and evolution is an effective method to ensure the quality of Web applications. In this paper, we apply Agent into this area, i.e. firstly, we explain the necessity and feasibility, and also give the general description of our method; then, we apply Agent into the Web performance testing, Web regression testing and Web usability evolution; conclusion remarks are given at last.