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386
Object Detection with Discriminatively Trained Part Based Models
"... We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their ..."
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Cited by 1422 (49 self)
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, 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
A discriminatively trained, multiscale, deformable part model
- In IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2008
, 2008
"... This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge ..."
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Cited by 555 (11 self)
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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
Sensitivity of Transfer Capability Margins
- IEEE Transactions on Power Systems
, 2002
"... Bulk power transfers in electric power systems are limited by transmission network security. Transfer capability measures the maximum power transfer permissible under certain assumptions. Once a transfer capability has been computed for one set of assumptions, it is useful to quickly estimate the ef ..."
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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
Digital Signatures for Flows and Multicasts
, 1999
"... We present chaining techniques for signing/verifying multiple packets using a single signing/verification operation. We then present flow signing and verification procedures based upon a tree chaining technique. Since a single signing/verification operation is amortized over many packets, these proc ..."
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Cited by 169 (2 self)
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, 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
Real-Time Wide-area Loading Margin Sensitivity (WALMS) in Power Systems
"... Abstract-Loading margin sensitivity (LMS) has been widely used in applications in the realm of voltage stability assessment. Typically, LMS is derived based on system equilibrium equations near bifurcation and therefore requires full detailed system model and significant computation effort. Availab ..."
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. 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
AN EFFICIENT SENSITIVITY ANALYSIS BASED METHOD FOR CALCULATING LOAD MARGINS TO VOLTAGE COLLAPSE
"... 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 to explore ..."
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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
Adjusting for nonignorable drop-out using semiparametric nonresponse models (with discussion
- Journal of the American Statistical Association
, 1999
"... Consider a study whose design calls for the study subjects to be followed from enrollment (time t = 0) to time t = T,at which point a primary endpoint of interest Y is to be measured. The design of the study also calls for measurements on a vector V(t) of covariates to be made at one or more times t ..."
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Cited by 120 (14 self)
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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
Financial constraints, asset tangibility, and corporate investment
- Review of Financial Studies
"... When firms are able to pledge their assets as collateral, investment and borrowing become endogenous: pledgeable assets support more borrowings that in turn allow for further investment in pledgeable assets. We show that this credit multiplier has a significant effect on investment when firms face c ..."
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Cited by 107 (9 self)
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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
A General Approach to Integrated Risk Management with Skewed, Fat-tailed Risks
, 2005
"... 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 the me ..."
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Cited by 73 (3 self)
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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
Recognition using Regions
"... This paper presents a unified framework for object detection, segmentation, and classification using regions. Region features are appealing in this context because: (1) they encode shape and scale information of objects naturally; (2) they are only mildly affected by background clutter. Regions have ..."
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Cited by 106 (5 self)
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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
Results 1 - 10
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386