In this paper we study the problem of bivariate density estimation. The aim is to find a density function with the smallest number of local extreme values which is adequate with ...
This paper develops easily computed, tight bounds on Generalized Linear Predictors and instrumental variable estimators when outcome data are partially identi…ed. A salient exam...
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
This paper studies the convergence of a fixed point iteration algorithm for the problem of max-min signal-to-interference ratio (SIR) balancing. Differently from the existing wor...
We present an NLP system that classifies the assertion type of medical problems in clinical notes used for the Fourth i2b2/VA Challenge. Our classifier uses a variety of linguisti...