Sciweavers

ICML
2010
IEEE
14 years 19 days ago
Music Plus One and Machine Learning
A system for musical accompaniment is presented in which a computer-driven orchestra follows and learns from a soloist in a concerto-like setting. The system is decomposed into th...
Christopher Raphael
ICML
2010
IEEE
14 years 19 days ago
Online Learning for Group Lasso
We develop a novel online learning algorithm for the group lasso in order to efficiently find the important explanatory factors in a grouped manner. Different from traditional bat...
Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Ly...
ICML
2010
IEEE
14 years 19 days ago
A New Analysis of Co-Training
In this paper, we present a new analysis on co-training, a representative paradigm of disagreement-based semi-supervised learning methods. In our analysis the co-training process ...
Wei Wang, Zhi-Hua Zhou
ICML
2010
IEEE
14 years 19 days ago
Projection Penalties: Dimension Reduction without Loss
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
Yi Zhang 0010, Jeff Schneider
ICML
2010
IEEE
14 years 19 days ago
The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
ICML
2010
IEEE
14 years 19 days ago
Online Streaming Feature Selection
We study an interesting and challenging problem, online streaming feature selection, in which the size of the feature set is unknown, and not all features are available for learni...
Xindong Wu, Kui Yu, Hao Wang, Wei Ding
ICML
2010
IEEE
14 years 19 days ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
ICML
2010
IEEE
14 years 19 days ago
Clustering processes
The problem of clustering is considered, for the case when each data point is a sample generated by a stationary ergodic process. We propose a very natural asymptotic notion of co...
Daniil Ryabko
ICML
2010
IEEE
14 years 19 days ago
Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
Daniel J. Lizotte, Michael H. Bowling, Susan A. Mu...