Papers
On the Asymptotic Distribution of the Minimum Empirical Risk
Jacob Westerhout, Trungtin Nguyen, Xin Guo et al.
On the Calibration of Human Pose Estimation
Kerui Gu, Rongyu Chen, Xuanlong Yu et al.
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
Yunyan Bai, Yuxing Liu, Luo Luo
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
On the Consistency of Kernel Methods with Dependent Observations
Pierre-François Massiani, Sebastian Trimpe, Friedrich Solowjow
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
Junyi Fan, Yuxuan Han, Zijian Liu et al.
On the Diminishing Returns of Width for Continual Learning
Etash Kumar Guha, Vihan Lakshman
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
On the Effectiveness of Supervision in Asymmetric Non-Contrastive Learning
Jeongheon Oh, Kibok Lee
On the Embedding Collapse when Scaling up Recommendation Models
Xingzhuo Guo, Junwei Pan, Ximei Wang et al.
On the Emergence of Cross-Task Linearity in Pretraining-Finetuning Paradigm
Zhanpeng Zhou, Zijun Chen, Yilan Chen et al.
On the Error-Propagation of Inexact Hotelling’s Deflation for Principal Component Analysis
Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum et al.
On the Expressive Power of Spectral Invariant Graph Neural Networks
Bohang Zhang, Lingxiao Zhao, Haggai Maron
On The Fairness Impacts of Hardware Selection in Machine Learning
Sree Harsha Nelaturu, Nishaanth Kanna Ravichandran, Cuong Tran et al.
On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors
Ruipeng Liu, Borui He, Naveed Tahir et al.
On the Generalization of Equivariant Graph Neural Networks
Rafal Karczewski, Amauri H Souza, Vikas Garg
On the Hardness of Probabilistic Neurosymbolic Learning
Jaron Maene, Vincent Derkinderen, Luc De Raedt
On the Identifiability of Switching Dynamical Systems
Carles Balsells-Rodas, Yixin Wang, Yingzhen Li
On the Implicit Bias of Adam
Matias D. Cattaneo, Jason Matthew Klusowski, Boris Shigida
On the Independence Assumption in Neurosymbolic Learning
Emile Van Krieken, Pasquale Minervini, Edoardo Ponti et al.
On the Last-Iterate Convergence of Shuffling Gradient Methods
Zijian Liu, Zhengyuan Zhou
On the Maximal Local Disparity of Fairness-Aware Classifiers
Jinqiu Jin, Haoxuan Li, Fuli Feng
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
Denys Pushkin, Raphaël Berthier, Emmanuel Abbe
On the Nonlinearity of Layer Normalization
Yunhao Ni, Yuxin Guo, Junlong Jia et al.