Papers
Optimal Approximation and Generalization Errors for Deep Convolutional Neural Networks
Jinxin Wang, Shao-Bo Lin
Investigating the Histogram Loss in Regression
Ehsan Imani, Kai Luedemann, Sam Scholnick-Hughes et al.
Bayes-Optimal Fair Classification with Linear Disparity Constraints via Pre-, In-, and Post-processing
Xianli Zeng, Kevin Jiang, Guang Cheng et al.
Why "Classic" Transformers Are Shallow and A Depth-Enabling Technique
Yueyao Yu, Yin Zhang
Kernel-based Distributed Learning
Heng Lian, Xu Guo
A Convex Framework for Confounding Robust Inference
Kei Ishikawa, Niao He, Takafumi Kanamori
Probabilistic Rainfall Downscaling: Joint Generalized Neural Models with Censored Spatial Gaussian Copula
David Huk, Rilwan A. Adewoyin, Ritabrata Dutta
Sparse Topic Modeling via Spectral Decomposition and Thresholding
Huy Tran, Yating Liu, Claire Donnat
Nonparametric generative modeling for time series via Schrödinger bridge
Mohamed Hamdouche, Pierre Henry-Labordère, Huyên Pham
Do We Need to Penalize Variance of Losses for Learning with Label Noise?
Yexiong Lin, Yu Yao, Yuxuan Du et al.
Causal Influences over Social Learning Networks
Mert Kayaalp, Ali H. Sayed
Neural Exploitation and Exploration of Contextual Bandits
Yikun Ban, Yuchen Yan, Arindam Banerjee et al.
Knowledge Cascade: Reverse Knowledge Distillation on Nonparametric Multivariate Functional Estimation
Luyang Fang, Haoran Lu, Yongkai Chen et al.
Inference with non-differentiable surrogate loss in a general high-dimensional classification framework
Muxuan Liang, Yang Ning, Maureen A Smith et al.
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks
Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna
The Role of Contextual Information in Best Arm Identification
Masahiro Kato, Kaito Ariu
Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective
Yuling Jiao, Yanming Lai, Yang Wang et al.
Online Bernstein-von Mises theorem
Jeyong Lee, Junhyeok Choi, Minwoo Chae
Covariate-dependent Hierarchical Dirichlet Processes
Huizi Zhang, Sara Wade, Natalia Bochkina
DCatalyst: A Unified Accelerated Framework for Decentralized Optimization
TIanyu Cao, Xiaokai Chen, Gesualdo Scutari
Boosted Control Functions: Distribution Generalization and Invariance in Confounded Models
Nicola Gnecco, Jonas Peters, Sebastian Engelke et al.
Contrasting Local and Global Modeling with Machine Learning and Satellite Data: A Case Study Estimating Tree Canopy Height in African Savannas
Esther Rolf, Lucia Gordon, Milind Tambe et al.
A Symplectic Analysis of Alternating Mirror Descent
Jonas E. Katona, Xiuyuan Wang, Andre Wibisono
Two-way Node Popularity Model for Directed and Bipartite Networks
Bing-Yi Jing, Ting Li, Jiangzhou Wang et al.