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Generalized iterative scaling

Known as: GIS (disambiguation), Improved iterative scaling 
In statistics, generalized iterative scaling (GIS) and improved iterative scaling (IIS) are two early algorithms used to fit log-linear models… 
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Related topics

Related topics

8 relations
AlgorithmConditional random fieldCoordinate descentExpectation–maximization algorithm

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Issues with Partially Matching Feature Functions in Conditional Exponential Models
Conditional Exponential Models (CEM) are effectively used in several machine learning approaches, e.g., in Conditional Random… 
2012
2012
An Iterative Scaling Algorithm for Maximum Entropy Reasoning in Relational Probabilistic Conditional Logic
Recently, different semantics for relational probabilistic conditionals and corresponding maximum entropy (ME) inference… 
2010
2010
Accelerating generalized iterative scaling using componentwise extrapolations for on-line conditional random fields
In this paper, a simple and globally convergent method based on penalized generalized iterative scaling (GIS) with staggered… 
2007
2007
An Extension of Iterative Scaling for Decision and Data Aggregation in Ensemble Classification
Improved iterative scaling (IIS) is an algorithm for learning maximum entropy (ME) joint and conditional probability models… 
2007
2007
Detecting Network Attacks via Improved Iterative Scaling
Network security has become a critical issue with the rapid increase in connectivity of computer systems over the Internet which… 
2007
2007
Propagating Image-Level Part Statistics to Enhance Object Detection
The bag-of-words approach has become increasingly attractive in the fields of object category recognition and scene… 
2005
2005
An Extension of Iterative Scaling for Joint Decision-Level and Feature-Level Fusion in Ensemble Classification
Improved iterative scaling (IIS) is a simple, powerful algorithm for learning maximum entropy (ME) conditional probability models… 
2004
2004
Maximum entropy direct model as a unified model for acoustic modeling in speech recognition
Traditional statistical models for speech recognition have been dominated by generative models such as Hidden Markov Models (HMMs… 
1998
1998
Statistical Inference for Probabilistic Constraint Logic Programming
Most approaches to probabilistic logic programming deal with deduction systems and xpoint semantics for programming systems with… 
Review
1996
Review
1996
Convexity, Maximum Likelihood and All That
This note is meant as a gentle but comprehensive introduction to the expectation-maximization (EM) and improved iterative scaling… 
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