Papers
572 papers found
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
Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs
Gellért Weisz, András György, Tadashi Kozuno et al.
Approximate Value Equivalence
Christopher Grimm, Andre Barreto, Satinder P. Singh
A Multilabel Classification Framework for Approximate Nearest Neighbor Search
Ville Hyvönen, Elias Jääsaari, Teemu Roos
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
Kruno Lehman, Alain Durmus, Umut Simsekli
SOAR: Improved Indexing for Approximate Nearest Neighbor Search
Philip Sun, David Simcha, Dave Dopson et al.
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
Hedi Hadiji, Sarah Sachs, Tim van Erven et al.
An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint
Mengzhao Wang, Lingwei Lv, Xiaoliang Xu et al.
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Ziyi Huang, Henry Lam, Amirhossein Meisami et al.
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
Emile van Krieken, Thiviyan Thanapalasingam, Jakub Tomczak et al.
Refined Mechanism Design for Approximately Structured Priors via Active Regression
Christos Boutsikas, Petros Drineas, Marios Mertzanidis et al.
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
Runa Eschenhagen, Alexander Immer, Richard Turner et al.
Approximately Equivariant Graph Networks
Ningyuan Huang, Ron Levie, Soledad Villar
Computing Approximate $\ell_p$ Sensitivities
Swati Padmanabhan, David Woodruff, Richard Zhang
Multi-Step Generalized Policy Improvement by Leveraging Approximate Models
Lucas N. Alegre, Ana Bazzan, Ann Nowe et al.
Differentially Private Approximate Near Neighbor Counting in High Dimensions
Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi et al.