Papers
4,025 papers found
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting
Louis Sharrock, Daniel Dodd, Christopher Nemeth
Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process
Lingkai Kong, Haotian Sun, Yuchen Zhuang et al.
Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting
Siyuan Xu, Yucheng Wang, Mingzhou Fan et al.
Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results
Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano et al.
Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters
Zhenyu Sun, Xiaochun Niu, Ermin Wei
Understanding Inverse Scaling and Emergence in Multitask Representation Learning
Muhammed E. Ildiz, Zhe Zhao, Samet Oymak
Understanding Progressive Training Through the Framework of Randomized Coordinate Descent
Rafał Szlendak, Elnur Gasanov, Peter Richtarik
Understanding the Generalization Benefits of Late Learning Rate Decay
Yinuo Ren, Chao Ma, Lexing Ying
Unsupervised Change Point Detection in Multivariate Time Series
Daoping Wu, Suhas Gundimeda, Shaoshuai Mou et al.
Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio
Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen et al.
Unveiling Latent Causal Rules: A Temporal Point Process Approach for Abnormal Event Explanation
Yiling Kuang, Chao Yang, Yang Yang et al.
Variational Gaussian Process Diffusion Processes
Prakhar Verma, Vincent Adam, Arno Solin
Variational Resampling
Oskar Kviman, Nicola Branchini, Víctor Elvira et al.
VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates
Guillaume Braun, Masashi Sugiyama
Vector Quantile Regression on Manifolds
Marco Pegoraro, Sanketh Vedula, Aviv A Rosenberg et al.
Warped Diffusion for Latent Differentiation Inference
Masahiro Nakano, Hiroki Sakuma, Ryo Nishikimi et al.
Weight-Sharing Regularization
Mehran Shakerinava, Motahareh MS Sohrabi, Siamak Ravanbakhsh et al.
When No-Rejection Learning is Consistent for Regression with Rejection
Xiaocheng Li, Shang Liu, Chunlin Sun et al.
Why is parameter averaging beneficial in SGD? An objective smoothing perspective
Atsushi Nitanda, Ryuhei Kikuchi, Shugo Maeda et al.
XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task Coverage
Jae-Jun Lee, Sung Whan Yoon
A Blessing of Dimensionality in Membership Inference through Regularization
Jasper Tan, Daniel LeJeune, Blake Mason et al.
A Bregman Divergence View on the Difference-of-Convex Algorithm
Oisin Faust, Hamza Fawzi, James Saunderson
A Case of Exponential Convergence Rates for SVM
Vivien Cabannnes, Stefano Vigogna