, their value had not been demonstrated on difficult benchmarks such as the PASCAL datasets. Our system relies on new methods for discriminative training with partially labeled data. We combine a margin-sensitive approach for data-mining hard negative examples with a formalism we call latent SVM. A latent SVM

training. We combine a margin-sensitive approach for data mining hard negative examples with a formalism we call latent SVM. A latent SVM, like a hidden CRF, leads to a non-convex training problem. However, a latent SVM is semi-convex and the training problem becomes convex once latent information

the effect on the transfer capability of modifying those assumptions. This paper presents a computationally efficient formula for the first order sensitivity of the transfer capability with respect to the variation of any parameters. The sensitivity formula is very fast to evaluate. The approach

, these procedures improve signing and verification rates by one to two orders of magnitude compared to the approach of signing/verifying packets individually. Our procedures do not depend upon reliable delivery of packets, provide delay-bounded signing, and are thus suitable for delay-sensitive flows and multicast

. Availability of phasor measurement units (PMUs) due to the recent development of wide-area monitoring system (WAMS) provides an alternative computation-friendly approach for calculating LMS. With such motivation, this work proposes measurementbased wide-area loading margin sensitivity (WALMS) in bulk power

ABSTRACT – In this paper an efficient method for calculating load margins to voltage collapse is proposed. The method consists of computing gradual load increases based on sensitivity analysis. It is well suited for large systems, since heuristics are added to the basic algorithm in order

the selection bias parameter α0 as known, rather than estimating it from the data. We then perform a sensitivity analysis to see how inference about µ0 changes as we vary α0 over a plausible range of values. We apply our approach to the analysis of ACTG 175, an AIDS clinical trial. KEY WORDS: Augmented inverse

us to use a “differences in differences ” approach to identify the effect of financing frictions on corporate investment: we compare the differential (marginal) effect of asset tangibility on the sensitivity of investment to cash flow across different regimes of financial constraints. Using two

Integrated risk management in a financial institution requires an approach for aggregating risk types (market, credit, and operational) whose distributional shapes vary considerably. In this paper, we construct the joint risk distribution for a typical large, internationally active bank using

region weights using a max-margin framework. In detection and segmentation, we apply a generalized Hough voting scheme to generate hypotheses of object locations, scales and support, followed by a verification classifier and a constrained segmenter on each hypothesis. The proposed approach significantly