'Initial state distribution' presentation slideshows

CS60057 Speech &Natural Language Processing

CS60057 Speech &Natural Language Processing. Autumn 2007. Lecture 11 17 August 2007. Hidden Markov Models. Bonnie Dorr Christof Monz CMSC 723: Introduction to Computational Linguistics Lecture 5 October 6, 2004.

1.21k views • 97 slides

Part of Speech Tagging & Hidden Markov Models

637 views • 48 slides

Approximate Inference 2: Monte Carlo Markov Chain

Approximate Inference 2: Monte Carlo Markov Chain. MCMC. Limitations of LW: Evidence affects sampling only for nodes that are its descendants For nondescendants, the weights account for the effect of the evidence

559 views • 35 slides

Dynamic Probabilistic Relational Models Paper by: Sumit Sanghai, Pedro Domingos, Daniel Weld

Dynamic Probabilistic Relational Models Paper by: Sumit Sanghai, Pedro Domingos, Daniel Weld. Anna Yershova yershova@uiuc.edu. Presentation slides are adapted from: Lise Getoor, Eyal Amir and Pedro Domingos slides. The problem. How to represent/model uncertain sequential phenomena?.

426 views • 33 slides

Large-Margin Feature Adaptation for Automatic Speech Recognition

Large-Margin Feature Adaptation for Automatic Speech Recognition. Chih-Chieh Cheng #1, Fei Sha 2 and Lawrence K. Saul #3 # Department of Computer Science and Engineering, University of California, San Diego 1 chc028@cs.ucsd.edu 3 saul@cs.ucsd.edu

340 views • 25 slides

Classifier-Based Approximate Policy Iteration

321 views • 21 slides

Objectives: Elements of a Discrete Model Evaluation Decoding Dynamic Programming

283 views • 15 slides

HMM-BASED PATTERN DETECTION

HMM-BASED PATTERN DETECTION. Image Processing and Reconstruction Winter 2002. Outline. Markov Process Hidden Markov Models Elements Basic Problems Evaluation Optimization Training Implementation 2-D HMM Application Simulation and Results. Markov Process.

263 views • 14 slides