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» On Clusterings - Good, Bad and Spectral
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NIPS
2007
13 years 10 months ago
DIFFRAC: a discriminative and flexible framework for clustering
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
Francis Bach, Zaïd Harchaoui
IEICET
2010
92views more  IEICET 2010»
13 years 7 months ago
Spectral Methods for Thesaurus Construction
Traditionally, popular synonym acquisition methods are based on the distributional hypothesis, and a metric such as Jaccard coefficients is used to evaluate the similarity between...
Nobuyuki Shimizu, Masashi Sugiyama, Hiroshi Nakaga...
ISAAC
2007
Springer
109views Algorithms» more  ISAAC 2007»
14 years 2 months ago
Separating Populations with Wide Data: A Spectral Analysis
In this paper, we consider the problem of partitioning a small data sample drawn from a mixture of k product distributions. We are interested in the case that individual features a...
Avrim Blum, Amin Coja-Oghlan, Alan M. Frieze, Shuh...
NIPS
2004
13 years 9 months ago
Blind One-microphone Speech Separation: A Spectral Learning Approach
We present an algorithm to perform blind, one-microphone speech separation. Our algorithm separates mixtures of speech without modeling individual speakers. Instead, we formulate ...
Francis R. Bach, Michael I. Jordan
ICCV
2009
IEEE
13 years 6 months ago
Building recognition using sketch-based representations and spectral graph matching
In this work, we address the problem of building recognition across two camera views with large changes in scales and viewpoints. The main idea is to construct a semantically rich...
Yu-Chia Chung, Tony X. Han, Zhihai He