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Person re-identification, i.e., recognizing a single person across spatially disjoint cameras, is an important task in visual… Expand This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a… Expand Sparse signal models have been the focus of much recent research, leading to (or improving upon) state-of-the-art results in… Expand We present a discriminative model for polyphonic piano transcription. Support vector machines trained on spectral features are… Expand When labelled training data is plentiful, discriminative techniques are widely used since they give excellent generalization… Expand This article considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of… Expand In this paper we present methods of enhancing existing discriminative classifiers for multi-labeled predictions. Discriminative… Expand Discriminative models have been preferred over generative models in many machine learning problems in the recent past owing to… Expand In this work we present discriminative random fields (DRFs), a discriminative framework for the classification of image regions… Expand In many supervised learning tasks, the entities to be labeled are related to each other in complex ways and their labels are not… Expand