Sciweavers

JMLR
2012
13 years 9 months ago
Maximum Margin Temporal Clustering
Temporal Clustering (TC) refers to the factorization of multiple time series into a set of non-overlapping segments that belong to k temporal clusters. Existing methods based on e...
Minh Hoai Nguyen, Fernando De la Torre
JMLR
2012
13 years 9 months ago
Wilks' phenomenon and penalized likelihood-ratio test for nonparametric curve registration
The problem of curve registration appears in many different areas of applications ranging from neuroscience to road traffic modeling. In the present work, we propose a nonparamet...
Arnak S. Dalalyan, Olivier Collier
JMLR
2012
13 years 9 months ago
Perturbation based Large Margin Approach for Ranking
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
Eunho Yang, Ambuj Tewari, Pradeep D. Ravikumar
JMLR
2012
13 years 9 months ago
Sparse Higher-Order Principal Components Analysis
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Genevera Allen
JMLR
2012
13 years 9 months ago
Transductive Learning of Structural SVMs via Prior Knowledge Constraints
Reducing the number of labeled examples required to learn accurate prediction models is an important problem in structured output prediction. In this paper we propose a new transd...
Chun-Nam Yu
JMLR
2012
13 years 9 months ago
Sample Complexity of Composite Likelihood
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
Joseph K. Bradley, Carlos Guestrin
JMLR
2012
13 years 9 months ago
Learning Fourier Sparse Set Functions
Peter Stobbe, Andreas Krause
JMLR
2012
13 years 9 months ago
PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits
We develop a new tool for data-dependent analysis of the exploration-exploitation trade-off in learning under limited feedback. Our tool is based on two main ingredients. The fi...
Yevgeny Seldin, Nicolò Cesa-Bianchi, Peter ...
JMLR
2012
13 years 9 months ago
Primal-Dual methods for sparse constrained matrix completion
We develop scalable algorithms for regular and non-negative matrix completion. In particular, we base the methods on trace-norm regularization that induces a low rank predicted ma...
Yu Xin, Tommi Jaakkola