Papers
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
Rasool Fakoor, Jonas W Mueller, Nick Erickson et al.
Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint
Georgios Amanatidis, Federico Fusco, Philip Lazos et al.
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms
Sascha Saralajew, Lars Holdijk, Thomas Villmann
Fast and Accurate $k$-means++ via Rejection Sampling
Vincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard et al.
Fast and Flexible Temporal Point Processes with Triangular Maps
Oleksandr Shchur, Nicholas Gao, Marin Biloš et al.
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev
Xiao Wang, Qi Lei, Ioannis Panageas
Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine
Jiajin Li, Caihua Chen, Anthony Man-Cho So
Faster DBSCAN via subsampled similarity queries
Heinrich Jiang, Jennifer Jang, Jakub Lacki
Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC
Arun Ganesh, Kunal Talwar
Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs
Agniva Chowdhury, Palma London, Haim Avron et al.
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence
Lénaïc Chizat, Pierre Roussillon, Flavien Léger et al.
Fast Fourier Convolution
Lu Chi, Borui Jiang, Yadong Mu
Fast geometric learning with symbolic matrices
Jean Feydy, Alexis Glaunès, Benjamin Charlier et al.
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
Geoff Pleiss, Martin Jankowiak, David Eriksson et al.
Fast Transformers with Clustered Attention
Apoorv Vyas, Angelos Katharopoulos, François Fleuret
Fast Unbalanced Optimal Transport on a Tree
Ryoma Sato, Makoto Yamada, Hisashi Kashima
f-Divergence Variational Inference
Neng Wan, Dapeng Li, NAIRA HOVAKIMYAN
Feature Importance Ranking for Deep Learning
Maksymilian Wojtas, Ke Chen
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests
Sean Kulinski, Saurabh Bagchi, David I Inouye
Federated Accelerated Stochastic Gradient Descent
Honglin Yuan, Tengyu Ma
Federated Bayesian Optimization via Thompson Sampling
Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Federated Principal Component Analysis
Andreas Grammenos, Rodrigo Mendoza Smith, Jon Crowcroft et al.
FedSplit: an algorithmic framework for fast federated optimization
Reese Pathak, Martin J. Wainwright
Few-Cost Salient Object Detection with Adversarial-Paced Learning
Dingwen Zhang, HaiBin Tian, Jungong Han
Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer Proxies
Yuehua Zhu, Muli Yang, Cheng Deng et al.