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Systems Competition and Network Effects
- JOURNAL OF ECONOMIC PERSPECTIVES—VOLUME 8, NUMBER 2—SPRING 1994—PAGES 93–115
, 1994
"... Many products have little or no value in isolation, but generate value when combined with others. Examples include: nuts and bolts, which together provide fastening services; home audio or video components and programming, which together provide entertainment services; automobiles, repair parts and ..."
Abstract
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Cited by 544 (6 self)
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on the behavior and performance of the variety of private and public institutions that arise in systems markets to influence expectations, facilitate coordination, and achieve compatibility. In many cases, the components purchased for a single system are spread over time, which means that rational buyers must
The Cornerstones of Competitive Advantage: A Resource Based View,
- Strategic Management Journal
, 1993
"... JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about J ..."
Abstract
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Cited by 978 (1 self)
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JSTOR, please contact support@jstor.org. This paper elucidates the underlying economics of the resource-based view of competitive advantage and integrates existing perspectives into a parsimonious model of resources and firm performance. The essence of this model is that four conditions underlie
Exploiting Generative Models in Discriminative Classifiers
- In Advances in Neural Information Processing Systems 11
, 1998
"... Generative probability models such as hidden Markov models provide a principled way of treating missing information and dealing with variable length sequences. On the other hand, discriminative methods such as support vector machines enable us to construct flexible decision boundaries and often resu ..."
Abstract
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Cited by 551 (9 self)
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result in classification performance superior to that of the model based approaches. An ideal classifier should combine these two complementary approaches. In this paper, we develop a natural way of achieving this combination by deriving kernel functions for use in discriminative methods such as support
Reasoning the fast and frugal way: Models of bounded rationality.
- Psychological Review,
, 1996
"... Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisncing, the authors have ..."
Abstract
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Cited by 611 (30 self)
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Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisncing, the authors
Modeling Strategic Relationships for Process Reengineering
, 1995
"... Existing models for describing a process (such as a business process or a software development process) tend to focus on the \what " or the \how " of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing and appr ..."
Abstract
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Cited by 550 (40 self)
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in terms of intentional dependency relationships among agents. Agents depend on each other for goals to be achieved, tasks to be performed, and resources to be furnished. Agents are intentional in that they have desires and wants, and strategic in that they are concerned about opportunities
A scheduling model for reduced CPU energy
- ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE
, 1995
"... The energy usage of computer systems is becoming an important consideration, especially for batteryoperated systems. Various methods for reducing energy consumption have been investigated, both at the circuit level and at the operating systems level. In this paper, we propose a simple model of job s ..."
Abstract
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Cited by 558 (3 self)
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an off-line algorithm that computes, for any set of jobs, a minimum-energy schedule. We then consider some on-line algorithms and their competitive performance for the power function P(s) = sp where p 3 2. It is shown that one natural heuristic, called the Average Rate heuristic, uses at most a constant
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 ..."
Abstract
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Cited by 555 (11 self)
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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
Shallow Parsing with Conditional Random Fields
, 2003
"... Conditional random fields for sequence labeling offer advantages over both generative models like HMMs and classifiers applied at each sequence position. Among sequence labeling tasks in language processing, shallow parsing has received much attention, with the development of standard evaluati ..."
Abstract
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Cited by 581 (8 self)
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evaluation datasets and extensive comparison among methods. We show here how to train a conditional random field to achieve performance as good as any reported base noun-phrase chunking method on the CoNLL task, and better than any reported single model. Improved training methods based on modern
A block-sorting lossless data compression algorithm
, 1994
"... We describe a block-sorting, lossless data compression algorithm, and our implementation of that algorithm. We compare the performance of our implementation with widely available data compressors running on the same hardware. The algorithm works by applying a reversible transformation to a block o ..."
Abstract
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Cited by 809 (5 self)
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statistical modelling techniques. The size of the input block must be large (a few kilobytes) to achieve good compression.
Imagenet classification with deep convolutional neural networks.
- In Advances in the Neural Information Processing System,
, 2012
"... Abstract We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 error rates of 37.5% and 17.0% which is considerably better than the pr ..."
Abstract
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Cited by 1010 (11 self)
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competition and achieved a winning top-5 test error rate of 15.3%, compared to 26.2% achieved by the second-best entry.
Results 1 - 10
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45,011
