Papers
4,025 papers found
Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch
Partha Talukdar, William Cohen
Scaling Nonparametric Bayesian Inference via Subsample-Annealing
Fritz Obermeyer, Jonathan Glidden, Eric Jonas
Selective Sampling with Drift
Edward Moroshko, Koby Crammer
Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process
Vikas Raykar, Priyanka Agrawal
Sketching the Support of a Probability Measure
Joachim Giesen, Soeren Laue, Lars Kuehne
SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication
Rebecca Steorts, Rob Hall, Stephen Fienberg
Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus
Vinny Davies, Richard Reeve, William Harvey et al.
Sparsity and the Truncated $l^2$-norm
Lee Dicker
Spoofing Large Probability Mass Functions to Improve Sampling Times and Reduce Memory Costs
Jon Parker, Hans Engler
Student-t Processes as Alternatives to Gaussian Processes
Amar Shah, Andrew Wilson, Zoubin Ghahramani
The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling
Willie Neiswanger, Frank Wood, Eric Xing
Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees
Jean Honorio, Tommi Jaakkola
Tilted Variational Bayes
James Hensman, Max Zwiessele, Neil D. Lawrence
To go deep or wide in learning?
Gaurav Pandey, Ambedkar Dukkipati
Towards building a Crowd-Sourced Sky Map
Dustin Lang, David Hogg, Bernhard Schölkopf
Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection
Jyri Kivinen, Chris Williams, Nicolas Heess
A Competitive Test for Uniformity of Monotone Distributions
Jayadev Acharya, Ashkan Jafarpour, Alon Orlitsky et al.
Active Learning for Interactive Visualization
Tomoharu Iwata, Neil Houlsby, Zoubin Ghahramani
A Last-Step Regression Algorithm for Non-Stationary Online Learning
Edward Moroshko, Koby Crammer
A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions
Prabhanjan Kambadur, Aurelie Lozano
A recursive estimate for the predictive likelihood in a topic model
James Scott, Jason Baldridge
A simple criterion for controlling selection bias
Eunice Yuh-Jie Chen, Judea Pearl
A simple sketching algorithm for entropy estimation over streaming data
Peter Clifford, Ioana Cosma
A unifying representation for a class of dependent random measures
Nicholas Foti, Joseph Futoma, Daniel Rockmore et al.
Bayesian learning of joint distributions of objects
Anjishnu Banerjee, Jared Murray, David Dunson