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David D. Cox
Researcher at IBM
Publications - 139
Citations - 14070
David D. Cox is an academic researcher from IBM. The author has contributed to research in topics: Cognitive neuroscience of visual object recognition & Artificial neural network. The author has an hindex of 44, co-authored 137 publications receiving 11084 citations. Previous affiliations of David D. Cox include Harvard University & University of Waterloo.
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Proceedings Article
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures
TL;DR: This work proposes a meta-modeling approach to support automated hyperparameter optimization, with the goal of providing practical tools that replace hand-tuning with a reproducible and unbiased optimization process.
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Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex.
David D. Cox,Robert L. Savoy +1 more
TL;DR: In the present study, multivariate statistical pattern recognition methods were used to classify patterns of fMRI activation evoked by the visual presentation of various categories of objects, demonstrating that fMRI data contain far more information than is typically appreciated.
Journal ArticleDOI
Visual Place Recognition: A Survey
Stephanie Lowry,Niko Sünderhauf,Paul Newman,John J. Leonard,David D. Cox,Peter Corke,Michael Milford +6 more
TL;DR: A survey of the visual place recognition research landscape is presented, introducing the concepts behind place recognition, how a “place” is defined in a robotics context, and the major components of a place recognition system.
Journal ArticleDOI
Untangling invariant object recognition.
James J. DiCarlo,David D. Cox +1 more
TL;DR: A graphical perspective is used to show that the primate ventral visual processing stream achieves a particularly effective solution in which single-neuron invariance is not the goal, and to speculate on the key neuronal mechanisms that could enable this solution.
Proceedings ArticleDOI
Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms
TL;DR: An introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization.