Papers
1,821 papers found
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models
Harikrishna Narasimhan, Andrew Cotter, Yichen Zhou et al.
Approximate Cross-Validation for Structured Models
Soumya Ghosh, Will Stephenson, Tin D Nguyen et al.
Approximate Cross-Validation with Low-Rank Data in High Dimensions
Will Stephenson, Madeleine Udell, Tamara Broderick
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
Hilal Asi, John C. Duchi
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
Andrew Foong, David Burt, Yingzhen Li et al.
Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games
Stephen Mcaleer, JB Lanier, Roy Fox et al.
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
Rui Zhang, Christian Walder, Edwin V. Bonilla et al.
Minibatch Stochastic Approximate Proximal Point Methods
Hilal Asi, Karan Chadha, Gary Cheng et al.
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
Nate Veldt, Austin R Benson, Jon M. Kleinberg
SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search
Qi Chen, Bing Zhao, Haidong Wang et al.
A variational approximate posterior for the deep Wishart process
Sebastian Ober, Laurence Aitchison
Approximate optimization of convex functions with outlier noise
Anindya De, Sanjeev Khanna, Huan Li et al.
Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces
Kirill Struminsky, Artyom Gadetsky, Denis Rakitin et al.
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes
Mohamad Amin Sharifi Kolarijani, Gyula Max, Peyman Mohajerin Esfahani
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm
Yasunori Akagi, Naoki Marumo, Hideaki Kim et al.
Faster Neural Network Training with Approximate Tensor Operations
Menachem Adelman, Kfir Levy, Ido Hakimi et al.
PCA Initialization for Approximate Message Passing in Rotationally Invariant Models
Marco Mondelli, Ramji Venkataramanan
Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht
Foundation Posteriors for Approximate Probabilistic Inference
Mike Wu, Noah Goodman
Approximate Secular Equations for the Cubic Regularization Subproblem
Yihang Gao, Man-Chung Yue, Michael Ng
Algorithms that Approximate Data Removal: New Results and Limitations
Vinith Suriyakumar, Ashia C Wilson
Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss
Aleksandros Sobczyk, Mathieu Luisier
AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators
Wenkai Xu, Gesine D Reinert