Papers
Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization
Yuchen Li, Laura Balzano, Deanna Needell et al.
Bayesian Inference of Contextual Bandit Policies via Empirical Likelihood
Jiangrong Ouyang, Mingming Gong, Howard Bondell
A causal fused lasso for interpretable heterogeneous treatment effects estimation
Oscar Hernan Madrid Padilla, Yanzhen Chen, Carlos Misael Madrid Padilla et al.
Unsupervised Feature Selection via Nonnegative Orthogonal Constrained Regularized Minimization
Yan Li, Defeng Sun, Liping Zhang
Reparameterized Complex-valued Neurons Can Efficiently Learn More than Real-valued Neurons via Gradient Descent
Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang et al.
Hierarchical Causal Models
Eli N. Weinstein, David M. Blei
Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection
Addison Kristanto Julistiono, Davoud Ataee Tarzanagh, Navid Azizan
Adaptive Forward Stepwise: A Method for High Sparsity Regression
Ivy Zhang, Robert Tibshirani
Optimization and Generalization of Gradient Descent for Shallow ReLU Networks with Minimal Width
Yunwen Lei, Puyu Wang, Yiming Ying et al.
Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection
Steven Adams, Andrea Patanè, Morteza Lahijanian et al.
CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration
Sophie Jaffard, Samuel Vaiter, Patricia Reynaud-Bouret
Exploring Novel Uncertainty Quantification through Forward Intensity Function Modeling
Yudong Wang, Zhi-Sheng Ye, Cheng Yong Tang
Generative Bayesian Inference with GANs
Yuexi Wang, Veronika Rockova
Communication-efficient Distributed Statistical Inference for Massive Data with Heterogeneous Auxiliary Information
Miaomiao Yu, Zhongfeng Jiang, Jiaxuan Li et al.
Decorrelated Local Linear Estimator: Inference for Non-linear Effects in High-dimensional Additive Models
Zijian Guo, Wei Yuan, Cunhui Zhang
Refined Risk Bounds for Unbounded Losses via Transductive Priors
Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy
A Common Interface for Automatic Differentiation
Guillaume Dalle, Adrian Hill
LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport
Lianghao Cao, Joshua Chen, Michael Brennan et al.
The Distribution of Ridgeless Least Squares Interpolators
Qiyang Han, Xiaocong Xu
Nonparametric Estimation of a Factorizable Density using Diffusion Models
Hyeok Kyu Kwon, Dongha Kim, Ilsang Ohn et al.
Learning Bayesian Network Classifiers to Minimize Class Variable Parameters
Shouta Sugahara, Koya Kato, James Cussens et al.
Simulation-based Calibration of Uncertainty Intervals under Approximate Bayesian Estimation
Terrance D. Savitsky, Julie Gershunskaya
An Anytime Algorithm for Good Arm Identification
Marc Jourdan, Andrée Delahaye-Duriez, Clémence Réda
Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classification
Aleksi Avela, Pauliina Ilmonen