Papers
23,522 papers found
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time
Michael D. Lee, Ian G. Fuss, Daniel J. Navarro
A Scalable Machine Learning Approach to Go
Lin Wu, Pierre F. Baldi
Subordinate class recognition using relational object models
Aharon B. Hillel, Daphna Weinshall
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression
Martin J. Wainwright, John D. Lafferty, Pradeep K. Ravikumar
Efficient Learning of Sparse Representations with an Energy-Based Model
Marc'aurelio Ranzato, Christopher Poultney, Sumit Chopra et al.
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields
Chi-hoon Lee, Shaojun Wang, Feng Jiao et al.
Clustering Under Prior Knowledge with Application to Image Segmentation
Dong S. Cheng, Vittorio Murino, Mário Figueiredo
Learning Structural Equation Models for fMRI
Enrico Simonotto, Heather Whalley, Stephen Lawrie et al.
Simplifying Mixture Models through Function Approximation
Kai Zhang, James T. Kwok
An Information Theoretic Framework for Eukaryotic Gradient Sensing
Joseph M. Kimmel, Richard M. Salter, Peter J. Thomas
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models
S. S. Keerthi, Vikas Sindhwani, Olivier Chapelle
Large Margin Component Analysis
Lorenzo Torresani, Kuang-chih Lee
Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Alan S. Willsky, Erik B. Sudderth, Martin J. Wainwright
A Bayesian Model of Conditioned Perception
Alan Stocker, Eero P. Simoncelli
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods
Alessandro Lazaric, Marcello Restelli, Andrea Bonarini
Modeling Natural Sounds with Modulation Cascade Processes
Richard Turner, Maneesh Sahani
Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing
Yuanhao Chen, Long Zhu, Chenxi Lin et al.
Catching Up Faster in Bayesian Model Selection and Model Averaging
Tim V. Erven, Steven D. Rooij, Peter Grünwald
Convex Clustering with Exemplar-Based Models
Danial Lashkari, Polina Golland
SpAM: Sparse Additive Models
Han Liu, Larry Wasserman, John D. Lafferty et al.
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Sebastian Gerwinn, Matthias Bethge, Jakob H. Macke et al.
Sparse deep belief net model for visual area V2
Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Zhengdong Lu, Cristian Sminchisescu, Miguel Á. Carreira-Perpiñán