Papers
4,122 papers found
Functional Linear Regression with Mixed Predictors
Daren Wang, Zifeng Zhao, Yi Yu et al.
Fundamental Limits and Tradeoffs in Invariant Representation Learning
Han Zhao, Chen Dan, Bryon Aragam et al.
Gaussian Process Boosting
Fabio Sigrist
Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits
Hao Chen, Lili Zheng, Raed Al Kontar et al.
Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression
Wenjia Wang, Bing-Yi Jing
Gauss-Legendre Features for Gaussian Process Regression
Paz Fink Shustin, Haim Avron
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
Fredrik D. Johansson, Uri Shalit, Nathan Kallus et al.
Generalized Ambiguity Decomposition for Ranking Ensemble Learning
Hongzhi Liu, Yingpeng Du, Zhonghai Wu
Generalized Matrix Factorization: efficient algorithms for fitting generalized linear latent variable models to large data arrays
Lukasz Kidzinski, Francis K.C. Hui, David I. Warton et al.
Generalized Resubstitution for Classification Error Estimation
Parisa Ghane, Ulisses Braga-Neto
Generalized Sparse Additive Models
Asad Haris, Noah Simon, Ali Shojaie
Getting Better from Worse: Augmented Bagging and A Cautionary Tale of Variable Importance
Lucas Mentch, Siyu Zhou
Globally Injective ReLU Networks
Michael Puthawala, Konik Kothari, Matti Lassas et al.
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
Shangtong Zhang, Remi Tachet des Combes, Romain Laroche
Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks
Alice Gatti, Zhixiong Hu, Tess Smidt et al.
Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences
Alan Chan, Hugo Silva, Sungsu Lim et al.
Hamilton-Jacobi equations on graphs with applications to semi-supervised learning and data depth
Jeff Calder, Mahmood Ettehad
Handling Hard Affine SDP Shape Constraints in RKHSs
Pierre-Cyril Aubin-Frankowski, Zoltan Szabo
IALE: Imitating Active Learner Ensembles
Christoffer Löffler, Christopher Mutschler
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning
Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias et al.
Improved Classification Rates for Localized SVMs
Ingrid Blaschzyk, Ingo Steinwart
Improved Generalization Bounds for Adversarially Robust Learning
Idan Attias, Aryeh Kontorovich, Yishay Mansour
Improving Bayesian Network Structure Learning in the Presence of Measurement Error
Yang Liu, Anthony C. Constantinou, Zhigao Guo
Information-Theoretic Characterization of the Generalization Error for Iterative Semi-Supervised Learning
Haiyun He, Hanshu Yan, Vincent Y. F. Tan
Information-theoretic Classification Accuracy: A Criterion that Guides Data-driven Combination of Ambiguous Outcome Labels in Multi-class Classification
Chihao Zhang, Yiling Elaine Chen, Shihua Zhang et al.