Spectral methods have greatly advanced the estimation of latent variable models, generating a sequence of novel and efficient algorithms with strong theoretical guarantees. However, current spectral algorithms are largely restricted to mixtures of discrete or Gaussian distributions. In this paper, we propose a kernel method for learning multi-view latent variable models, allowing each mixture c...

Interesting equalities have recently been discovered about latent tree models. They relate distributions of two or three observed variables with joint distributions of four or more observed variables, and with model parameters that depend on latent variables. The equations are derived by using matrix and tensor decompositions. This paper sheds new light on the equalities by offering an alternat...

We use the polynomial approach of Fuhrmann to construct explicit first-order input/latent variable/output realizations for systems with several operators acting on a function space. The class of systems being covered includes certain types of delay-differential, partial differential, and discrete-time mD-systems.

This chapter provides an introduction to models of human pose and motion for use in 3D human pose tracking. We concentrate on probabilistic latent variable models of kinematics, most of which are learned from motion capture data, and on recent physics-based models. We briefly discuss important open problems and future research challenges.

I review recent work in the statistics literature on instrumental variables methods from an econometrics perspective. I discuss some of the older, economic, applications including supply and demand models and relate them to the recent applications in settings of randomized experiments with noncompliance. I discuss the assumptions underlying instrumental variables methods and in what settings th...

Curiosity is a vital metacognitive skill in educational contexts. Yet, little is known about how social factors influence curiosity in group work. We argue that curiosity is evoked not only through individual, but also interpersonal activities, and present what we believe to be the first theoretical framework that articulates an integrated sociocognitive account of curiosity based on literature...

This paper presents an application of vision-based monitoring of long-term care facility residents. We develop an algorithm to detect events of interest, particularly falls by elderly residents. The algorithm uses a max-margin latent variable approach with spatiotemporal locations of the person in the video as latent variables. The recently developed Action Bank descriptor is utilized as a rich...

We present an approach for pricing of illiquid bonds (and bond derivatives) in an arbitrage-free way and consistently with observed prices of liquid bonds. The basic model is a multifactor term structure model with abstract latent factors. The approach is based on stochastic filtering techniques, leading to a continuous update of the distribution of the latent factors on the basis of the inform...

Based on the phenomena of mutual influence between participants of a face-to-face conversation, we propose a context-based prediction approach for modeling visual backchannels. Our goal is to create intelligent virtual listeners with the ability of providing backchannel feedbacks, enabling natural and fluid interactions. In our proposed approach, we first anticipate the speaker behaviors, and t...