Scene parsing is the problem of assigning a semantic label to every pixel in an image. Though an ambitious task, impressive advances have been made in recent years, in particular in scalable nonparametric techniques suitable for open-universe databases. This paper presents the CollageParsing algorithm for scalable nonparametric scene parsing. In contrast to common practice in recent nonparametr...

In this paper we consider the problem of estimating nonparametric panel data models with fixed effects. We introduce an iterative nonparametric kernel estimator. We also extend the estimation method to the case of a semiparametric partially linear fixed effects model. To determine whether a parametric, semiparametric or nonparametric model is appropriate, we propose test statistics to test betw...

This paper establishes the global asymptotic equivalence between the nonparametric regression with random design and the white noise under sharp smoothness conditions on an unknown regression or drift function. The asymptotic equivalence is established by constructing explicit equivalence mappings between the nonparametric regression and the white-noise experiments, which provide synthetic obse...

This paper establishes the global asymptotic equivalence between the nonparametric regression with random design and the white noise under sharp smoothness conditions on an unknown regression or drift function. The asymptotic equivalence is established by constructing explicit equivalence mappings between the nonparametric regression and the whitenoise experiments, which provide synthetic obser...

This paper makes three contributions to the literature on the nonparametric estimation of diffusion processes. First, we show that the nonparametric estimator of the drift function proposed by Stanton (J. of Finance, 1997) is not consistent. Second, we show that a proposed alternative nonparametric estimator of the drift function converges to the true drift in probability, in addition to provid...