Papers
Assumption-lean and data-adaptive post-prediction inference
Jiacheng Miao, Xinran Miao, Yixuan Wu et al.
Bagged Regularized k-Distances for Anomaly Detection
Yuchao Cai, Hanfang Yang, Yuheng Ma et al.
Four Axiomatic Characterizations of the Integrated Gradients Attribution Method
Daniel Lundstrom, Meisam Razaviyayn
Fast Algorithm for Constrained Linear Inverse Problems
Mohammed Rayyan Sheriff, Floor Fenne Redel, Peyman Mohajerin Esfahani
High-Rank Irreducible Cartesian Tensor Decomposition and Bases of Equivariant Spaces
Shihao Shao, Yikang Li, Zhouchen Lin et al.
Best Linear Unbiased Estimate from Privatized Contingency Tables
Jordan Awan, Adam Edwards, Paul Bartholomew et al.
Interpretable Global Minima of Deep ReLU Neural Networks on Sequentially Separable Data
Thomas Chen, Patrícia Muñoz Ewald
Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods
Bertille FOLLAIN, Francis BACH
Data-Driven Performance Guarantees for Classical and Learned Optimizers
Rajiv Sambharya, Bartolomeo Stellato
Contextual Bandits with Stage-wise Constraints
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett
Boosting Causal Additive Models
Maximilian Kertel, Nadja Klein
Frequentist Guarantees of Distributed (Non)-Bayesian Inference
Bohan Wu, César A. Uribe
Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection
Daiqi Gao, Yufeng Liu, Donglin Zeng
EMaP: Explainable AI with Manifold-based Perturbations
Minh Nhat Vu, Huy Quang Mai, My T. Thai
Autoencoders in Function Space
Justin Bunker, Mark Girolami, Hefin Lambley et al.
Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds
Paul Rosa, Judith Rousseau
System Neural Diversity: Measuring Behavioral Heterogeneity in Multi-Agent Learning
Matteo Bettini, Ajay Shankar, Amanda Prorok
Distribution Estimation under the Infinity Norm
Aryeh Kontorovich, Amichai Painsky
Extending Temperature Scaling with Homogenizing Maps
Christopher Qian, Feng Liang, Jason Adams
Density Estimation Using the Perceptron
Patrik Róbert Gerber, Tianze Jiang, Yury Polyanskiy et al.
Simplex Constrained Sparse Optimization via Tail Screening
Peng Chen, Jin Zhu, Junxian Zhu et al.
Score-Based Diffusion Models in Function Space
Jae Hyun Lim, Nikola B. Kovachki, Ricardo Baptista et al.
Regularized Rényi Divergence Minimization through Bregman Proximal Gradient Algorithms
Thomas Guilmeau, Emilie Chouzenoux, Víctor Elvira
WEFE: A Python Library for Measuring and Mitigating Bias in Word Embeddings
Pablo Badilla, Felipe Bravo-Marquez, María José Zambrano et al.
Frontiers to the learning of nonparametric hidden Markov models
Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet