Matrix factorization is one of the best approaches for collaborative filtering, because of its high accuracy in presenting users and items latent factors. The main disadvantages of matrix factorization are its complexity, and being very hard to be parallelized, specially with very large matrices. In this paper, we introduce a new method for collaborative filtering based on Matrix Factorization ...

Reseña por Andrea Szulc y Pía Levy

This paper illustrates how to compare different agent-based models and how to compare an agent-based model with real data. As examples we investigate ARFIMA models, the probability density function, and the spectral density function. We illustrate the methodology in an analysis of the agent-based model developed by Levy, Levy, Solomon (2000), and confront it with the S&P 500 for a comparison wi...

Levy Institute scholars and conference participants. The purpose of the series is to disseminate ideas to and elicit comments from academics and professionals. Levy Economics Institute of Bard College, founded in 1986, is a nonprofit, nonpartisan, independently funded research organization devoted to public service. Through scholarship and economic research it generates viable, effective public...

In this paper, we propose an importance-sampling based method to obtain an unbiased simulator to evaluate expectations involving random variables whose probability density functions are unknown while their Fourier transforms have an explicit form. We give a general principle about how to choose appropriate importance samplers under different models. Compared with the existing methods, our metho...

ABSTRACT In this paper, the classic Levy identification method is reviewed and reformulated using a complex representation. This new formulation is able to solve the well known bias of the classic method at low frequencies. The formulation is generic, addressing both integer order and fractional order transfer functions. A new algorithm based on a stacked matrix and its pseudo-inverse is propos...

This work is devoted to the study of the statistical properties of financial indices from developed and emergent markets. We performed a new analysis of the behavior of several financial indices by using a normalized truncated Levy walk model. We conclude that the truncated Levy distribution describes perfectly the evolution of the financial indices near a crash for both well-developed and emer...

This paper reports that bursty hot spot sizes are a key factor in causing the heavy-tail distribution of flights in human walks. A heavy-tailed distribution of flights is a signature feature of Levy walks. The data analysis based on GPS traces of human walks reveals that the sizes of a few extremely large hot spots are dominating the mean size of hot spots and they cause the bursty (i.e., long-...