Papers
176,624 papers found
Predicting a Switching Sequence of Graph Labelings
Mark Herbster, Stephen Pasteris, Massimiliano Pontil
Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions
Jimmy Lei Ba, Kevin Swersky, Sanja Fidler et al.
Predicting Eye Fixations Using Convolutional Neural Networks
Nian Liu, Junwei Han, Dingwen Zhang et al.
Predicting Good Features for Image Geo-Localization Using Per-Bundle VLAD
Hyo Jin Kim, Enrique Dunn, Jan-Michael Frahm
Predicting Multiple Structured Visual Interpretations
Debadeepta Dey, Varun Ramakrishna, Martial Hebert et al.
Predicting Preference Reversals via Gaussian Process Uncertainty Aversion
Rikiya Takahashi, Tetsuro Morimura
Predicting the Future Behavior of a Time-Varying Probability Distribution
Christoph H. Lampert
Prediction of Search Targets From Fixations in Open-World Settings
Hosnieh Sattar, Sabine Muller, Mario Fritz et al.
Predictive Entropy Search for Bayesian Optimization with Unknown Constraints
Jose Miguel Hernandez-Lobato, Michael Gelbart, Matthew Hoffman et al.
Predictive Inverse Optimal Control for Linear-Quadratic-Gaussian Systems
Xiangli Chen, Brian Ziebart
Predtron: A Family of Online Algorithms for General Prediction Problems
Prateek Jain, Nagarajan Natarajan, Ambuj Tewari
Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons
Dohyung Park, Joe Neeman, Jin Zhang et al.
Preference Relation-based Markov Random Fields for Recommender Systems
Shaowu Liu, Gang Li, Truyen Tran et al.
Preferential Attachment in Graphs with Affinities
Jay Lee, Manzil Zaheer, Stephan Günnemann et al.
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
Jonas W Mueller, Tommi Jaakkola
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric
Vivien Seguy, Marco Cuturi
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Yu-Xiang Wang, Stephen Fienberg, Alex Smola
Privacy Preserving Optics for Miniature Vision Sensors
Francesco Pittaluga, Sanjeev J. Koppal
Private Graphon Estimation for Sparse Graphs
Christian Borgs, Jennifer Chayes, Adam Smith
Probabilistic Appearance Models for Segmentation and Classification
Julia Kruger, Jan Ehrhardt, Heinz Handels
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
Jose Miguel Hernandez-Lobato, Ryan Adams
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process
Ye Wang, David B Dunson
Probabilistic Label Relation Graphs With Ising Models
Nan Ding, Jia Deng, Kevin P. Murphy et al.