Sciweavers

NIPS
2003
14 years 6 days ago
Margin Maximizing Loss Functions
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
Saharon Rosset, Ji Zhu, Trevor Hastie
AAAI
2006
14 years 8 days ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
NIPS
2008
14 years 8 days ago
Privacy-preserving logistic regression
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
Kamalika Chaudhuri, Claire Monteleoni
ESEM
2008
ACM
14 years 19 days ago
A hybrid faulty module prediction using association rule mining and logistic regression analysis
This paper proposes a fault-prone module prediction method that combines association rule mining with logistic regression analysis. In the proposed method, we focus on three key m...
Yasutaka Kamei, Akito Monden, Shuuji Morisaki, Ken...
CLEF
2008
Springer
14 years 19 days ago
Logistic Regression for Metadata: Cheshire Takes on Adhoc-TEL
In this paper we will briefly describe the approaches taken by the Berkeley Cheshire Group for the Adhoc-TEL 2008 tasks (Mono and Bilingual retrieval). Since the AdhocTEL task is ...
Ray R. Larson
CLEF
2008
Springer
14 years 19 days ago
Cheshire at GeoCLEF 2008: Text and Fusion Approaches for GIR
In this paper we will briefly describe the approaches taken by Berkeley for the main GeoCLEF 2008 tasks (Mono and Bilingual retrieval). The approach this year used probabilistic t...
Ray R. Larson
ECRIME
2007
14 years 2 months ago
A comparison of machine learning techniques for phishing detection
There are many applications available for phishing detection. However, unlike predicting spam, there are only few studies that compare machine learning techniques in predicting ph...
Saeed Abu-Nimeh, Dario Nappa, Xinlei Wang, Suku Na...
ECML
2003
Springer
14 years 4 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank
ICML
2004
IEEE
14 years 4 months ago
Ensembles of nested dichotomies for multi-class problems
Nested dichotomies are a standard statistical technique for tackling certain polytomous classification problems with logistic regression. They can be represented as binary trees ...
Eibe Frank, Stefan Kramer
CEAS
2005
Springer
14 years 4 months ago
Implicit Queries for Email
Implicit query systems examine a document and automatically conduct searches for the most relevant information. In this paper, we offer three contributions to implicit query resea...
Joshua Goodman, Vitor R. Carvalho