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Random field
Results: 650

#	Item
221	Structure-Perceptron Learning of a Hierarchical Log-Linear Model Long (Leo) Zhu Department of Statistics University of California, Los Angeles Yuanhao Chen Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2008-04-06 19:12:13 Artificial intelligence Neural networks Computational statistics Perceptron Segmentation Active appearance model Supervised learning Conditional random field Shape context Machine learning Computer vision Statistics
222	Max Margin AND/OR Graph Learning for Parsing the Human Body Long (Leo) Zhu Department of Statistics University of California, Los Angeles Yuanhao Chen Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2008-04-06 20:05:24 Theoretical computer science Electromagnetism Topology Connectivity Applied mathematics Electronics Segmentation-based object categorization Graphical models Conditional random field Machine learning
223	VIBRATION FIELD OF A DOUBLE-LEAF PLATE WITH RANDOM PARAMETER FUNCTIONS Hyuck Chung School of Computing and Mathematical Sciences, Auckland University of Technology, PB 92006, Auckland, New Zealand Add to Reading List Source URL: www.acoustics.asn.au Language: English - Date: 2013-01-07 00:01:21 Vibration Normal distribution Partial differential equation Fourier transform Spectral density Variance Fourier series Expected value Bessel function Mathematical analysis Fourier analysis Joseph Fourier
224	Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing Long (Leo) Zhu Department of Statistics University of California at Los Angeles Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2008-06-10 16:49:54 Artificial intelligence Graphical models Statistical models Bioinformatics Constellation model Expectation–maximization algorithm Conditional random field Bayesian network Supervised learning Statistics Machine learning Probability and statistics
225	Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing Yuanhao Chen Department of Automation University of Science and Technology of China Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2008-01-11 19:07:08 Probability theory Networks Applied mathematics Belief propagation Coding theory Topology Tree Connectivity Markov random field Graph theory Graphical models Mathematics
226	Recursive Segmentation and Recognition Templates for 2D Parsing Long (Leo) Zhu CSAIL MIT Add to Reading List Source URL: people.csail.mit.edu Language: English - Date: 2008-10-13 13:50:19 Learning Perceptron Pattern recognition Segmentation Conditional random field Margin classifier Statistical classification Natural language processing Parsing Machine learning Statistics Artificial intelligence
227	CLASSIFICATION AND RECOGNITION WITH DIRECT SEGMENT MODELS Geoffrey Zweig Microsoft Research ABSTRACT Segment based direct models have recently been used to improve the output of existing state-of-the Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2012-01-17 14:29:12 Machine learning Computational linguistics Statistical models Graphical models Speech recognition N-gram Generative model Conditional random field Segmentation Science Statistics Probability and statistics
228	1646 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 28, Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2006-08-28 13:27:03 Probability theory Artificial intelligence Markov random field Theoretical computer science Chordal graph Tree decomposition Clique Matching Belief propagation Graph theory Graph operations Graphical models
229	Formic: Cost-efficient and Scalable Prototyping of Manycore Architectures Spyros Lyberis, George Kalokerinos, Michalis Lygerakis, Vassilis Papaefstathiou, Dimitris Tsaliagkos, Manolis Katevenis, Dionisios Pnevmatikatos a Add to Reading List Source URL: www.ics.forth.gr Language: English - Date: 2013-12-23 07:16:59 Computer memory Field-programmable gate array MicroBlaze Xilinx CPU cache Multi-core processor Dynamic random-access memory Joint Test Action Group NetFPGA Computer hardware Computing Electronic engineering
230	Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling Feng Jiao University of Waterloo Abstract We present a new semi-supervised training Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2006-12-28 15:24:48 Statistical theory Estimation theory Conditional random field Theoretical computer science Supervised learning Kullback–Leibler divergence Semi-supervised learning Expectation–maximization algorithm Conditional entropy Statistics Machine learning Information theory

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