Papers
Topology Selection in Graphical Models of Autoregressive Processes
Jitkomut Songsiri, Lieven Vandenberghe
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM
Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang et al.
Tree Decomposition for Large-Scale SVM Problems
Fu Chang, Chien-Yang Guo, Xiao-Rong Lin et al.
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubramanian
Using Contextual Representations to Efficiently Learn Context-Free Languages
Alexander Clark, Rémi Eyraud, Amaury Habrard
WEKA−Experiences with a Java Open-Source Project
Remco R. Bouckaert, Eibe Frank, Mark A. Hall et al.
Why Does Unsupervised Pre-training Help Deep Learning?
Dumitru Erhan, Yoshua Bengio, Aaron Courville et al.
Adaptive False Discovery Rate Control under Independence and Dependence
Gilles Blanchard, É
A Least-squares Approach to Direct Importance Estimation
Takafumi Kanamori, Shohei Hido, Masashi Sugiyama
An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity
Jose M. Peña, Roland Nilsson, Johan Björkegren et al.
Analysis of Perceptron-Based Active Learning
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni
An Analysis of Convex Relaxations for MAP Estimation of Discrete MRFs
M. Pawan Kumar, Vladimir Kolmogorov, Philip H.S. Torr
An Anticorrelation Kernel for Subsystem Training in Multiple Classifier Systems
Luciana Ferrer, Kemal Sönmez, Elizabeth Shriberg
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
Jacob Abernethy, Francis Bach, Theodoros Evgeniou et al.
Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification
Eitan Greenshtein, Junyong Park
A Survey of Accuracy Evaluation Metrics of Recommendation Tasks
Asela Gunawardana, Guy Shani
Bayesian Network Structure Learning by Recursive Autonomy Identification
Raanan Yehezkel, Boaz Lerner
Bounded Kernel-Based Online Learning
Francesco Orabona, Joseph Keshet, Barbara Caputo
CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning
Roberto Esposito, Daniele P. Radicioni
Cautious Collective Classification
Luke K. McDowell, Kalyan Moy Gupta, David W. Aha
Classification with Gaussians and Convex Loss
Dao-Hong Xiang, Ding-Xuan Zhou
Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors
Mathias Drton, Michael Eichler, Thomas S. Richardson
Consistency and Localizability
Alon Zakai, Ya'acov Ritov