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ICML
2009
IEEE
10 years 8 months ago
A Bayesian approach to protein model quality assessment
Given multiple possible models b1, b2, . . . bn for a protein structure, a common sub-task in in-silico Protein Structure Prediction is ranking these models according to their qua...
Hetunandan Kamisetty, Christopher James Langmead
ICML
2009
IEEE
10 years 8 months ago
On sampling-based approximate spectral decomposition
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
ICML
2009
IEEE
10 years 8 months ago
Deep transfer via second-order Markov logic
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
Jesse Davis, Pedro Domingos
ICML
2009
IEEE
10 years 8 months ago
Learning instance specific distances using metric propagation
In many real-world applications, such as image retrieval, it would be natural to measure the distances from one instance to others using instance specific distance which captures ...
De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou
ICML
2009
IEEE
10 years 8 months ago
Discriminative k-metrics
The k q-flats algorithm is a generalization of the popular k-means algorithm where q dimensional best fit affine sets replace centroids as the cluster prototypes. In this work, a ...
Arthur Szlam, Guillermo Sapiro
ICML
2009
IEEE
10 years 8 months ago
Robust feature extraction via information theoretic learning
In this paper, we present a robust feature extraction framework based on informationtheoretic learning. Its formulated objective aims at simultaneously maximizing the Renyi's...
Xiaotong Yuan, Bao-Gang Hu
ICML
2009
IEEE
10 years 8 months ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis
ICML
2009
IEEE
10 years 8 months ago
Optimal reverse prediction: a unified perspective on supervised, unsupervised and semi-supervised learning
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
Linli Xu, Martha White, Dale Schuurmans
ICML
2009
IEEE
10 years 8 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis
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