PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Steve Gunn

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Number of EPrints submitted by this user: 34

Machine Learning applied to Text Analysis: Overview
Eric Gaussier and Nicola Cancedda
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Memory-Based Shallow Parsing for Text Mining
Walter Daelemans
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Text Mining
Marko Grobelnik and Dunja Mladenić
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Kernel Methods for Natural Language Processing
Jean-Michel Renders
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Linear Programming Boosting for Uneven Datasets
Jure Leskovec and John Shawe-Taylor
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Text Categorization via Ellipsoid Separation
Andriy Kharechko, John Shawe-Taylor, Ralf Herbrich and Thore Graepel
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

A Bayesian Framework for Hierarchical Classification
Nicolò Cesa-Bianchi, Alex Conconi and Claudio Gentile
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Mining the Semantic Web: Requirements for Machine Learning
Fabio Ciravegna
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Probabilistic Textual Entailment: Generic Applied Modeling of Language Variability
Ido Dagan and Oren Glickman
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Efficient Computation of Gap-weighted String Kernels on Large Alphabets
Juho Rousu and John Shawe-Taylor
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Highlighting Latent Structures in Text
Michèle Jardino
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Learning Topic Hierarchies and Thematic Annotations from Document Collections
Hermine Njike-Fotzo and Patrick Gallinari
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Theme-Topic Mixture Model for Document Representation
Mikaela Keller and Samy Bengio
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Combining Clustering with Canonical Correlation Analysis for Cross-Language Patent Retrieval
Yaoyong Li and John Shawe-Taylor
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

A Methodology for Topographic Clustering of Structured Text Documents
Marie-Jeanne Lesot, Delphine Dard and Florence d'Alché-Buc
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Bayesian Networks for Structured Information retrieval
Benjamin Piwowarski, Trang Vu and Patrick Gallinari
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.

Toward Adaptive, Personalized Computing: Directions and Frontiers
Eric Horvitz
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Minimizing Calibration Efforts for an Indoor 802.11 Device Location Measurement System
John Krumm and John Platt
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Probabilistic Machine Listening for Interactive Music Performance Systems
Ali Cemgil and Ben Kröse
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Probabilistic Models and Continuous Dynamics
John Williamson
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Challenges and Opportunities for Reinforcement Learning in Human Computer Interaction Systems
Satinder Baveja
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Optimizing Call Routing by Integrating Spoken Dialog Models with Queuing Models
Tim Paek
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Improving Meetings with Microphone Array Algorithms
Ivan Tashev
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Recognition of Multimodal Group Actions in Meetings
Iain McCowan, Daniel Gatica-Perez, Samy Bengio and Guillaume Lathoud
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Web Personalization with Machine Learning
Corey Anderson
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Automatically Generating User Interfaces
Krzysztof Gajos
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Retrieving a User Language Model from an Unsupervised Document Map
Mikko Kurimo and Krista Lagus
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Vision for Multimodal Conversational Interfaces
Trevor Darrell
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Relevance Feedback from Eye Movements for Proactive IR
Jarkko Salojärvi, Kai Puolamäki and Samuel Kaski
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Joint Design of Data Analysis Algorithms and User Interface for Video Applications
Nebojsa Jojic, Sumit Basu, Nemanja Petrovic, Brendan Frey and Thomas Huang
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Signal Extraction for Brain-Computer Interface
David Hardoon and John Shawe-Taylor
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Enhancing Brain-Computer Interfaces by Machine Learning Techniques
Benjamin Blankertz, Guido Dornhege, Steven Lemm, Gabriel Curio and Klaus-Robert Müller
In: Machine Learning Meets the User Interface, 12 December 2003, Whistler, Canada.

Band Selection for Hyperspectral Image Classification using Mutual Information
Baofeng Guo, Steve Gunn, Bob Damper and James Nelson
IEEE Geoscience and Remote Sensing Letters Volume 3, Number 4, pp. 522-526, 2006.

Machine Learning Can Improve Prediction of Severity in Acute Pancreatitis using Admission Values of APACHE II Score and C-Reactive Protein.
Callum Pearce, Steve Gunn, Adil Ahmed and Colin Johnson
Pancreatology pp. 123-131, 2006.