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Probabilistic Graphical Models - Principles and Techniques
The framework of probabilistic graphical models, presented in this book, provides a general approach for causal reasoning and decision making under uncertainty, allowing interpretable models to be constructed and then manipulated by reasoning algorithms.
The Genotype-Tissue Expression (GTEx) project
The Genotype-Tissue Expression (GTEx) project is described, which will establish a resource database and associated tissue bank for the scientific community to study the relationship between genetic variation and gene expression in human tissues.
Support Vector Machine Active Learning with Applications to Text Classification
Experimental results showing that employing the active learning method can significantly reduce the need for labeled training instances in both the standard inductive and transductive settings are presented.
FastSLAM: a factored solution to the simultaneous localization and mapping problem
This paper presents FastSLAM, an algorithm that recursively estimates the full posterior distribution over robot pose and landmark locations, yet scales logarithmically with the number of landmarks in the map.
Max-Margin Markov Networks
Maximum margin Markov (M3) networks incorporate both kernels, which efficiently deal with high-dimensional features, and the ability to capture correlations in structured data, and a new theoretical bound for generalization in structured domains is provided.
SCAPE: shape completion and animation of people
- Dragomir Anguelov, P. Srinivasan, D. Koller, S. Thrun, J. Rodgers, James Davis
- Computer ScienceInternational Conference on Computer Graphics and…
- 1 July 2005
The SCAPE method is capable of constructing a high-quality animated surface model of a moving person, with realistic muscle deformation, using just a single static scan and a marker motion capture sequence of the person.
Self-Paced Learning for Latent Variable Models
A novel, iterative self-paced learning algorithm where each iteration simultaneously selects easy samples and learns a new parameter vector that outperforms the state of the art method for learning a latent structural SVM on four applications.
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The landscape of gene expression across tissues is described, thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants are cataloged, complex network relationships are described, and signals from genome-wide association studies explained by eQTLs are identified.
Toward Optimal Feature Selection
An efficient algorithm for feature selection which computes an approximation to the optimal feature selection criterion is given, showing that the algorithm effectively handles datasets with a very large number of features.
Decomposing a scene into geometric and semantically consistent regions
- Stephen Gould, Richard Fulton, D. Koller
- Computer ScienceIEEE International Conference on Computer Vision
- 1 September 2009
A region-based model which combines appearance and scene geometry to automatically decompose a scene into semantically meaningful regions and which achieves state-of-the-art performance on the tasks of both multi-class image segmentation and geometric reasoning.