Papers
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro et al.
Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics
Jarren Briscoe, Garrett Kepler, Daryl Robert DeFord et al.
A Likelihood Based Approach for Watermark Detection
Xingchi Li, Guanxun Li, Xianyang Zhang
AlleNoise - large-scale text classification benchmark dataset with real-world label noise
Alicja Rączkowska, Aleksandra Osowska-Kurczab, Jacek Szczerbiński et al.
All models are wrong, some are useful: Model Selection with Limited Labels
Patrik Okanovic, Andreas Kirsch, Jannes Kasper et al.
All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling
Emanuele Marconato, Sebastien Lachapelle, Sebastian Weichwald et al.
Almost linear time differentially private release of synthetic graphs
Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
Paul Edmund Chang, Nasrulloh Ratu Bagus Satrio Loka, Daolang Huang et al.
A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models
Xiaoyan Hu, Ho-fung Leung, Farzan Farnia
A Multi-Task Learning Approach to Linear Multivariate Forecasting
Liran Nochumsohn, Hedi Zisling, Omri Azencot
An Adaptive Method for Weak Supervision with Drifting Data
Alessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda et al.
Analysis of Two-Stage Rollout Designs with Clustering for Causal Inference under Network Interference
Mayleen Cortez-Rodriguez, Matthew Eichhorn, Christina Yu
Analyzing Generative Models by Manifold Entropic Metrics
Daniel Galperin, Ullrich Koethe
Analyzing the Role of Permutation Invariance in Linear Mode Connectivity
Keyao Zhan, Puheng Li, Lei Wu
An Empirical Bernstein Inequality for Dependent Data in Hilbert Spaces and Applications
Erfan Mirzaei, Andreas Maurer, Vladimir R Kostic et al.
An Iterative Algorithm for Rescaled Hyperbolic Functions Regression
Yeqi Gao, Zhao Song, Junze Yin
A Novel Convex Gaussian Min Max Theorem for Repeated Features
David Bosch, Ashkan Panahi
Ant Colony Sampling with GFlowNets for Combinatorial Optimization
Minsu Kim, Sanghyeok Choi, Hyeonah Kim et al.
Anytime-Valid A/B Testing of Counting Processes
Michael Lindon, Nathan Kallus
Application of Structured State Space Models to High energy physics with locality sensitive hashing
Cheng Jiang, Sitian Qian
Approximate Equivariance in Reinforcement Learning
Jung Yeon Park, Sujay Bhatt, Sihan Zeng et al.
Approximate Global Convergence of Independent Learning in Multi-Agent Systems
Ruiyang Jin, Zaiwei Chen, Yiheng Lin et al.
Approximate information maximization for bandit games
Alex Barbier Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson et al.
Approximating the Total Variation Distance between Gaussians
Arnab Bhattacharyya, Weiming Feng, Piyush Srivastava
A primer on linear classification with missing data
Angel David REYERO LOBO, Alexis Ayme, Claire Boyer et al.