Papers
4,122 papers found
Fast Screening Rules for Optimal Design via Quadratic Lasso Reformulation
Guillaume Sagnol, Luc Pronzato
FedLab: A Flexible Federated Learning Framework
Dun Zeng, Siqi Liang, Xiangjing Hu et al.
Finding Groups of Cross-Correlated Features in Bi-View Data
Miheer Dewaskar, John Palowitch, Mark He et al.
Finite-time Koopman Identifier: A Unified Batch-online Learning Framework for Joint Learning of Koopman Structure and Parameters
Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares
First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems
Michael I. Jordan, Tianyi Lin, Manolis Zampetakis
Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation
Xu Han, Xiaohui Chen, Francisco J. R. Ruiz et al.
Flexible Model Aggregation for Quantile Regression
Rasool Fakoor, Taesup Kim, Jonas Mueller et al.
FLIP: A Utility Preserving Privacy Mechanism for Time Series
Tucker McElroy, Anindya Roy, Gaurab Hore
Foundation Models and Fair Use
Peter Henderson, Xuechen Li, Dan Jurafsky et al.
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
Zongyi Li, Daniel Zhengyu Huang, Burigede Liu et al.
From Understanding Genetic Drift to a Smart-Restart Mechanism for Estimation-of-Distribution Algorithms
Weijie Zheng, Benjamin Doerr
Functional L-Optimality Subsampling for Functional Generalized Linear Models with Massive Data
Hua Liu, Jinhong You, Jiguo Cao
GANs as Gradient Flows that Converge
Yu-Jui Huang, Yuchong Zhang
Gap Minimization for Knowledge Sharing and Transfer
Boyu Wang, Jorge A. Mendez, Changjian Shui et al.
Gaussian Processes with Errors in Variables: Theory and Computation
Shuang Zhou, Debdeep Pati, Tianying Wang et al.
Generalization Bounds for Adversarial Contrastive Learning
Xin Zou, Weiwei Liu
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels
Hao Wang, Rui Gao, Flavio P. Calmon
Generalization error bounds for multiclass sparse linear classifiers
Tomer Levy, Felix Abramovich
Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data
Di Wang, Lijie Hu, Huanyu Zhang et al.
Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables
Hamid Mousavi, Jakob Drefs, Florian Hirschberger et al.
GFlowNet Foundations
Yoshua Bengio, Salem Lahlou, Tristan Deleu et al.
Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation
Cynthia Rudin, Yaron Shaposhnik