Text Classification using String Kernels (2008)
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Chris Watkins
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Computing Confidence Measures in Stochastic Logic Programs (2008)
Abstract. Stochastic logic programs (SLPs) provide an efficient representation for complex tasks such as modelling metabolic pathways. In recent years, methods have been developed to perform...
of Machine Learning: namely Support Vector Machines (SVMs) and Inductive (2008)
Stephen Muggleton, Huma Lodhi, Ata Amini
Abstract. In this paper we explore a topic which is at the intersection of two areas
of Machine Learning: namely Support Vector Machines (SVMs) and Inductive (2008)
Stephen Muggleton, Huma Lodhi, Ata Amini
Abstract. In this paper we explore a topic which is at the intersection of two areas
Boosting Strategy for Classification (2008)
Huma Lodhi, Grigoris Karakoulas, John Shawe-taylor
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifiers in terms of the...
ABSTRACT Automatic Scientific Text Classification Using Local Patterns: (2007)
Kdd Cup (task, Moustafa M. Ghanem, Yike Guo, Huma Lodhi, Yong Zhang
In this paper, we describe our approach for addressing Task 1 in the KDD CUP 2002 competition. The approach is based on developing and using an improved automatic feature selection method in...
Text Classification using String Kernels Text Classification using String Kernels (2007)
Huma Lodhi, Craig Saunders, Nello Cristianini, Chris Watkins, Pack Kaelbling
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
in Neural and Computational Learning II, (2007)
Huma Lodhi, John Shawe-taylor, Nello Cristianini, Chris Watkins
For more information see the NeuroCOLT website
in Neural and Computational Learning II, (2007)
Nello Cristianini, Huma Lodhi, John Shawe-taylor
For more information see the NeuroCOLT website
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S.H.: Is mutagenesis still challenging (2005)
Abstract. Mutagenesis is a well-known benchmark machine learning dataset. In this paper we present an overview of results for various methods applied to this dataset. In particular, we present a new...
Support vector inductive logic programming (2005)
Stephen Muggleton, Huma Lodhi, Ata Amini
1 Introduction In this paper we propose a novel machine learning approach which combines the di-mensionality independence advantages of Support Vector Machines (SVMs) with the expressive power and...
Modelling metabolic pathways using stochastic logic programs-based ensemble methods (2004)
Abstract. In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble learning....
Modelling metabolic pathways using stochastic logic programs-based ensemble methods (2004)
Abstract. In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble learning....
Paolo Frasconi, Andrea Passerini, Stephen Muggleton, Huma Lodhi
We introduce a declarative approach to kernel design based on background knowledge expressed in the form of logic programs. The theoretical foundation of declarative kernels is mereotopology, a...
Modelling metabolic pathways using stochastic logic programs-based ensemble methods (2004)
Abstract. In this paper we present a methodology to estimate rates of enzymatic reactions in metabolic pathways. Our methodology is based on applying stochastic logic learning in ensemble learning....
Paolo Frasconi, Andrea Passerini, Stephen Muggleton, Huma Lodhi
We introduce a declarative approach to kernel design based on background knowledge expressed in the form of logic programs. The theoretical foundation of declarative kernels is mereotopology, a...
Automatic Scientific Text Classification Using Local Patterns (2003)
Moustafa M. Ghanem, Yike Guo, Huma Lodhi, Yong Zhang
In this paper, we describe our approach for addressing Task 1 in the KDD CUP 2002 competition. The approach is based on developing and using an improved automatic feature selection method in...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini, Chris Watkins, Bernhard Schölkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, Nello Cristianini, Chris Watkins, Bernhard Scholkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, Nello Cristianini, Chris Watkins, Bernhard Scholkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, John Shawe-taylor, Nello Cristianini, Chris Watkins
We introduce a novel kernel for comparing two text documents. The kernel is an inner product in the feature space consisting of all subsequences of length k. A subsequence is any ordered sequence of...
Text classification using string kernels (2002)
Huma Lodhi, John Shawe-taylor, Nello Cristianini
1 Introduction Standard learning systems (like neural networks or decision trees) operate on input data after they have been transformed into feature vectors x1;:::; x ` 2 X from an n dimensional...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini, Chris Watkins, Bernhard Schölkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini, Chris Watkins, Bernhard Schölkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text Classification using String Kernels (2001)
Lodhi, Huma, Shawe-Taylor, John, Cristianini, Nello, Watkins, Chris
Text Classification using String Kernels (2001)
Lodhi, Huma, Shawe-Taylor, John, Cristianini, Nello, Watkins, Chris