Papers
4,025 papers found
Regret Bounds for Gaussian Process Bandit Problems
Steffen Grünewälder, Jean–Yves Audibert, Manfred Opper et al.
Risk Bounds for Levy Processes in the PAC-Learning Framework
Chao Zhang, Dacheng Tao
Semi-Supervised Learning via Generalized Maximum Entropy
Ayse Erkan, Yasemin Altun
Semi-Supervised Learning with Max-Margin Graph Cuts
Branislav Kveton, Michal Valko, Ali Rahimi et al.
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures
Yener Ulker, Bilge Günsel, Taylan Cemgil
Simple Exponential Family PCA
Jun Li, Dacheng Tao
Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms
Nevena Lazic, Brendan Frey, Parham Aarabi
State-Space Inference and Learning with Gaussian Processes
Ryan Turner, Marc Deisenroth, Carl Rasmussen
Structured Prediction Cascades
David Weiss, Benjamin Taskar
Structured Sparse Principal Component Analysis
Rodolphe Jenatton, Guillaume Obozinski, Francis Bach
Sufficient covariates and linear propensity analysis
Hui Guo, Philip Dawid
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation
Taiji Suzuki, Masashi Sugiyama
Supervised Dimension Reduction Using Bayesian Mixture Modeling
Kai Mao, Feng Liang, Sayan Mukherjee
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Guillaume Desjardins, Aaron Courville, Yoshua Bengio et al.
The Feature Selection Path in Kernel Methods
Fuxin Li, Cristian Sminchisescu
The Group Dantzig Selector
Han Liu, Jian Zhang, Xiaoye Jiang et al.
Towards Understanding Situated Natural Language
Antoine Bordes, Nicolas Usunier, Ronan Collobert et al.
Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot, Yoshua Bengio
Unsupervised Aggregation for Classification Problems with Large Numbers of Categories
Ivan Titov, Alexandre Klementiev, Kevin Small et al.
Variational methods for Reinforcement Learning
Thomas Furmston, David Barber
Why are DBNs sparse?
Shaunak Chatterjee, Stuart Russell
Why Does Unsupervised Pre-training Help Deep Learning?
Dumitru Erhan, Aaron Courville, Yoshua Bengio et al.