Specific supply-chain investments are vital in achieving faster lead-time performance and more competitive costs. In practice, such as in the highly leveraged telecom sector, the coordinating original equipment manufacturers (OEM) often delegate the upstream coordination of suppliers to contract manufacturers. This can be justified by informational advantages or economies of scale. However, the...

We propose to train Hidden Markov Model (HMM) by allocating Gaussian kernels non-uniformly across states so as to optimize a selected discriminative training criterion. The optimal kernel allocation problem is first formulated based upon a non-discriminative, Maximum Likelihood (ML) criterion and then generalized to incorporate discriminative ones. An effective kernel exchange algorithm is deri...

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse...

Previous studies have demonstrated that methylphenidate, MDMA (3,4-methylenedioxymethamphetamine), and other psychostimulants exert stimulant-like subjective effects in humans. Furthermore, MDMA and methylphenidate substitute for the discriminative stimulus effects of psychostimulants, such as amphetamine and cocaine, in animals, which suggests that MDMA and methylphenidate may produce similar ...

human action recognition is an important problem in computer vision. one of the methods that are recently used is sparse coding. conventional sparse coding algorithms learn dictionaries and codes in an unsupervised manner and neglect class information that is available in the training set. but in this paper for solving this problem, we use a discriminative sparse code based on multi-manifolds. ...

We study multiple unit Discriminative auctions when the bidders share logconcave utility functions and investigate the effects of bidders risk preferences on their bid functions when all bidders share a common utility function and when the bidders exhibit different risk preferences. We extend the existing findings from single unit auctions to multiple unit Discriminative auctions,from concave u...

Fair discriminative pedestrian finders are now available. In fact, these pedestrian finders make most errors on pedestrians in configurations that are uncommon in the training data, for example, mounting a bicycle. This is undesirable. However, the human configuration can itself be estimated discriminatively using structure learning. We demonstrate a pedestrian finder which first finds the most...

Stance detection is the task of classifying the attitude Previous work has assumed that either the target is mentioned in the text or that training data for every target is given. This paper considers the more challenging version of this task, where targets are not always mentioned and no training data is available for the test targets. We experiment with conditional LSTM encoding, which builds...

In this paper, we present a discriminative approach for reranking discourse trees generated by an existing probabilistic discourse parser. The reranker relies on tree kernels (TKs) to capture the global dependencies between discourse units in a tree. In particular, we design new computational structures of discourse trees, which combined with standard TKs, originate novel discourse TKs. The emp...