Papers
Dynamic angular synchronization under smoothness constraints
Ernesto Araya, Mihai Cucuringu, Hemant Tyagi
Derivative-Informed Neural Operator Acceleration of Geometric MCMC for Infinite-Dimensional Bayesian Inverse Problems
Lianghao Cao, Thomas O'Leary-Roseberry, Omar Ghattas
Wasserstein F-tests for Frechet regression on Bures-Wasserstein manifolds
Haoshu Xu, Hongzhe Li
Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis
Youcheng Niu, Jinming Xu, Ying Sun et al.
Learning causal graphs via nonlinear sufficient dimension reduction
Eftychia Solea, Bing Li, Kyongwon Kim
On Consistent Bayesian Inference from Synthetic Data
Ossi Räisä, Joonas Jälkö, Antti Honkela
Optimization Over a Probability Simplex
James Chok, Geoffrey M. Vasil
Laplace Meets Moreau: Smooth Approximation to Infimal Convolutions Using Laplace's Method
Ryan J. Tibshirani, Samy Wu Fung, Howard Heaton et al.
Sampling and Estimation on Manifolds using the Langevin Diffusion
Karthik Bharath, Alexander Lewis, Akash Sharma et al.
Sharp Bounds for Sequential Federated Learning on Heterogeneous Data
Yipeng Li, Xinchen Lyu
Local Linear Recovery Guarantee of Deep Neural Networks at Overparameterization
Yaoyu Zhang, Leyang Zhang, Zhongwang Zhang et al.
Stabilizing Sharpness-Aware Minimization Through A Simple Renormalization Strategy
Chengli Tan, Jiangshe Zhang, Junmin Liu et al.
Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process
Feifei Wang, Zimeng Zhao, Ruimin Ye et al.
Deletion Robust Non-Monotone Submodular Maximization over Matroids
Paul Dütting, Federico Fusco, Silvio Lattanzi et al.
Instability, Computational Efficiency and Statistical Accuracy
Nhat Ho, Koulik Khamaru, Raaz Dwivedi et al.
Estimation of Local Geometric Structure on Manifolds from Noisy Data
Yariv Aizenbud, Barak Sober
Ontolearn---A Framework for Large-scale OWL Class Expression Learning in Python
Caglar Demir, Alkid Baci, N'Dah Jean Kouagou et al.
Continuously evolving rewards in an open-ended environment
Richard M. Bailey
Recursive Causal Discovery
Ehsan Mokhtarian, Sepehr Elahi, Sina Akbari et al.
Evaluation of Active Feature Acquisition Methods for Time-varying Feature Settings
Henrik von Kleist, Alireza Zamanian, Ilya Shpitser et al.
On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations
Antoine Godichon-Baggioni, Nicklas Werge
Determine the Number of States in Hidden Markov Models via Marginal Likelihood
Yang Chen, Cheng-Der Fuh, Chu-Lan Michael Kao
Variance-Aware Estimation of Kernel Mean Embedding
Geoffrey Wolfer, Pierre Alquier
Scaling ResNets in the Large-depth Regime
Pierre Marion, Adeline Fermanian, Gérard Biau et al.
A Comparative Evaluation of Quantification Methods
Tobias Schumacher, Markus Strohmaier, Florian Lemmerich