Sciweavers

ECML
2006
Springer
13 years 9 months ago
Efficient Large Scale Linear Programming Support Vector Machines
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
Suvrit Sra
ECML
2006
Springer
13 years 9 months ago
B-Matching for Spectral Clustering
We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...
Tony Jebara, Vlad Shchogolev
ECML
2006
Springer
13 years 9 months ago
Reinforcement Learning for MDPs with Constraints
In this article, I will consider Markov Decision Processes with two criteria, each defined as the expected value of an infinite horizon cumulative return. The second criterion is e...
Peter Geibel
ECML
2006
Springer
13 years 9 months ago
Cascade Evaluation of Clustering Algorithms
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
Laurent Candillier, Isabelle Tellier, Fabien Torre...
ECML
2006
Springer
13 years 9 months ago
Pertinent Background Knowledge for Learning Protein Grammars
Christopher H. Bryant, Daniel Fredouille, Alex Wil...
COLT
2005
Springer
13 years 9 months ago
Data Dependent Concentration Bounds for Sequential Prediction Algorithms
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...
Tong Zhang
COLT
2005
Springer
13 years 9 months ago
Loss Bounds for Online Category Ranking
Category ranking is the task of ordering labels with respect to their relevance to an input instance. In this paper we describe and analyze several algorithms for online category r...
Koby Crammer, Yoram Singer
COLT
2005
Springer
13 years 9 months ago
From External to Internal Regret
External regret compares the performance of an online algorithm, selecting among N actions, to the performance of the best of those actions in hindsight. Internal regret compares ...
Avrim Blum, Yishay Mansour
COLT
2006
Springer
13 years 9 months ago
Can Entropic Regularization Be Replaced by Squared Euclidean Distance Plus Additional Linear Constraints
There are two main families of on-line algorithms depending on whether a relative entropy or a squared Euclidean distance is used as a regularizer. The difference between the two f...
Manfred K. Warmuth
COLT
2006
Springer
13 years 9 months ago
The Shortest Path Problem Under Partial Monitoring
András György, Tamás Linder, Gy...