Papers
572 papers found
On fast approximate submodular minimization
Stefanie Jegelka, Hui Lin, Jeff A. Bilmes
Sparse Approximate Manifolds for Differential Geometric MCMC
Ben Calderhead, Mátyás A. Sustik
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning
Ulugbek Kamilov, Sundeep Rangan, Michael Unser et al.
Non-parametric Approximate Dynamic Programming via the Kernel Method
Nikhil Bhat, Vivek Farias, Ciamac C. Moallemi
Approximate Gaussian process inference for the drift function in stochastic differential equations
Andreas Ruttor, Philipp Batz, Manfred Opper
An Approximate, Efficient LP Solver for LP Rounding
Srikrishna Sridhar, Stephen Wright, Christopher Re et al.
Approximate Inference in Continuous Determinantal Processes
Raja Hafiz Affandi, Emily B. Fox, Ben Taskar
Low-rank matrix reconstruction and clustering via approximate message passing
Ryosuke Matsushita, Toshiyuki Tanaka
Approximate Dynamic Programming Finally Performs Well in the Game of Tetris
Victor Gabillon, Mohammad Ghavamzadeh, Bruno Scherrer
Beyond Pairwise: Provably Fast Algorithms for Approximate $k$-Way Similarity Search
Anshumali Shrivastava, Ping Li
Approximate inference in latent Gaussian-Markov models from continuous time observations
Botond Cseke, Manfred Opper, Guido Sanguinetti
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
Vikash K Mansinghka, Tejas D Kulkarni, Yura N Perov et al.
On Prior Distributions and Approximate Inference for Structured Variables
Oluwasanmi O Koyejo, Rajiv Khanna, Joydeep Ghosh et al.
Clamping Variables and Approximate Inference
Adrian Weller, Tony Jebara
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition
Cameron Musco, Christopher Musco
Exactness of Approximate MAP Inference in Continuous MRFs
Nicholas Ruozzi
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods
Andrej Risteski, Yuanzhi Li
Iterative Refinement of the Approximate Posterior for Directed Belief Networks
Devon Hjelm, Ruslan Salakhutdinov, Kyunghyun Cho et al.
Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach
Remi Lam, Karen Willcox, David H. Wolpert
Maximization of Approximately Submodular Functions
Thibaut Horel, Yaron Singer
Guided Policy Search via Approximate Mirror Descent
William H Montgomery, Sergey Levine
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference
Jonathan Huggins, Ryan P. Adams, Tamara Broderick
Approximate Supermodularity Bounds for Experimental Design
Luiz Chamon, Alejandro Ribeiro
A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening
Kevin Lin, James L Sharpnack, Alessandro Rinaldo et al.