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AISTATS 2025

A

International Conference on Artificial Intelligence and Statistics

Official site ↗
584
accepted papers
1,956
authors
May 3-5, 2025
dates
Thailand
location

300 / 584 papers

  1. 1
    A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
    Ossi Räisä
    ,
    Antti Honkela
  2. 2
    A Causal Framework for Evaluating Deferring Systems
    Filippo Palomba
    ,
    Andrea Pugnana
    ,
    José M. Álvarez
    ,
    Salvatore Ruggieri
  3. 3
    A Computation-Efficient Method of Measuring Dataset Quality based on the Coverage of the Dataset
    Beomjun Kim
    ,
    Jaehwan Kim
    ,
    Kangyeon Kim
    ,
    Sunwoo Kim
    ,
    Heejin Ahn
  4. 4
    A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks
    Uday Kiran Reddy Tadipatri
    ,
    Benjamin David Haeffele
    ,
    Joshua Agterberg
    ,
    René Vidal
  5. 5
    A Differential Inclusion Approach for Learning Heterogeneous Sparsity in Neuroimaging Analysis
    Wenjing Han
    ,
    Yueming Wu
    ,
    Xinwei Sun
    ,
    Lingjing Hu
    ,
    Yizhou Wang
  6. 6
    A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
    Takahiro Kawashima
    ,
    Hideitsu Hino
  7. 7
    A Generalized Theory of Mixup for Structure-Preserving Synthetic Data
    Chungpa Lee
    ,
    Jongho Im
    ,
    Joseph H. T. Kim
  8. 8
    A graphical global optimization framework for parameter estimation of statistical models with nonconvex regularization functions
    Danial Davarnia
    ,
    Mohammadreza Kiaghadi
  9. 9
    A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
    Kasimir Tanner
    ,
    Matteo Vilucchio
    ,
    Bruno Loureiro
    ,
    Florent Krzakala
  10. 10
    A Likelihood Based Approach for Watermark Detection
    Xingchi Li
    ,
    Guanxun Li
    ,
    Xianyang Zhang
  11. 11
    A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models
    Xiaoyan Hu
    ,
    Ho-fung Leung
    ,
    Farzan Farnia
  12. 12
    A Multi-Task Learning Approach to Linear Multivariate Forecasting
    Liran Nochumsohn
    ,
    Hedi Zisling
    ,
    Omri Azencot
  13. 13
    A Novel Convex Gaussian Min Max Theorem for Repeated Features
    David Bosch
    ,
    Ashkan Panahi
  14. 14
    A primer on linear classification with missing data
    Angel David Reyero Lobo
    ,
    Alexis Ayme
    ,
    Claire Boyer
    ,
    Erwan Scornet
  15. 15
    A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
    Yatin Dandi
    ,
    Luca Pesce
    ,
    Hugo Cui
    ,
    Florent Krzakala
    ,
    Yue M. Lu
    ,
    Bruno Loureiro
  16. 16
    A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries
    Ashkan Soleymani
    ,
    Behrooz Tahmasebi
    ,
    Stefanie Jegelka
    ,
    Patrick Jaillet
  17. 17
    A Safe Bayesian Learning Algorithm for Constrained MDPs with Bounded Constraint Violation
    Krishna Chaitanya Kalagarla
    ,
    Rahul Jain
    ,
    Pierluigi Nuzzo
  18. 18
    A Safe Exploration Approach to Constrained Markov Decision Processes
    Tingting Ni
    ,
    Maryam Kamgarpour
  19. 19
    A Shapley-value Guided Rationale Editor for Rationale Learning
    Zixin Kuang
    ,
    Meng-Fen Chiang
    ,
    Wang-Chien Lee
  20. 20
    A Shared Low-Rank Adaptation Approach to Personalized RLHF
    Renpu Liu
    ,
    Peng Wang
    ,
    Donghao Li
    ,
    Cong Shen
    ,
    Jing Yang
  21. 21
    A Subquadratic Time Approximation Algorithm for Individually Fair k-Center
    Matthijs Ebbens
    ,
    Nicole Funk
    ,
    Jan Höckendorff
    ,
    Christian Sohler
    ,
    Vera Weil
  22. 22
    A Theoretical Framework for Preventing Class Collapse in Supervised Contrastive Learning
    Chungpa Lee
    ,
    Jeongheon Oh
    ,
    Kibok Lee
    ,
    Jy-yong Sohn
  23. 23
    A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstration
    Yingqian Cui
    ,
    Pengfei He
    ,
    Xianfeng Tang
    ,
    Qi He
    ,
    Chen Luo
    ,
    Jiliang Tang
    ,
    Yue Xing
  24. 24
    A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage
    François Bachoc
    ,
    Tommaso Cesari
    ,
    Roberto Colomboni
  25. 25
    A Unified Evaluation Framework for Epistemic Predictions
    Shireen Kudukkil Manchingal
    ,
    Muhammad Mubashar
    ,
    Kaizheng Wang
    ,
    Fabio Cuzzolin
  26. 26
    A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
    Khimya Khetarpal
    ,
    Zhaohan Daniel Guo
    ,
    Bernardo Ávila Pires
    ,
    Yunhao Tang
    ,
    Clare Lyle
    ,
    Mark Rowland
    ,
    Nicolas Heess
    ,
    Diana L. Borsa
    ,
    Arthur Guez
    ,
    Will Dabney
  27. 27
    Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties
    David Martínez-Rubio
    ,
    Christophe Roux
    ,
    Christopher Criscitiello
    ,
    Sebastian Pokutta
  28. 28
    Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation
    Amartya Sanyal
    ,
    Yaxi Hu
    ,
    Yaodong Yu
    ,
    Yian Ma
    ,
    Yixin Wang
    ,
    Bernhard Schölkopf
  29. 29
    Achieving $\widetilde{\mathcal{O}}(\sqrt{T})$ Regret in Average-Reward POMDPs with Known Observation Models
    Alessio Russo
    ,
    Alberto Maria Metelli
    ,
    Marcello Restelli
  30. 30
    Active Bipartite Ranking with Smooth Posterior Distributions
    James Cheshire
    ,
    Stéphan Clémençon
  31. 31
    Active Feature Acquisition for Personalised Treatment Assignment
    Julianna Piskorz
    ,
    Nicolás Astorga
    ,
    Jeroen Berrevoets
    ,
    Mihaela van der Schaar
  32. 32
    Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach
    Dheeraj Baby
    ,
    Boran Han
    ,
    Shuai Zhang
    ,
    Cuixiong Hu
    ,
    Bernie Wang
    ,
    Yuxiang Wang
  33. 33
    Adaptive Convergence Rates for Log-Concave Maximum Likelihood
    Gil Kur
    ,
    Aditya Guntuboyina
  34. 34
    Adaptive Extragradient Methods for Root-finding Problems under Relaxed Assumptions
    Yang Luo
    ,
    Michael J. O'Neill
  35. 35
    Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
    Xinxing Shi
    ,
    Thomas Baldwin-McDonald
    ,
    Mauricio A. Álvarez
  36. 36
    Additive Model Boosting: New Insights and Path(ologie)s
    Rickmer Schulte
    ,
    David Rügamer
  37. 37
    ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning
    Kaan Ozkara
    ,
    Bruce Huang
    ,
    Ruida Zhou
    ,
    Suhas N. Diggavi
  38. 38
    Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data
    Hongni Wang
    ,
    Junxi Zhang
    ,
    Na Li
    ,
    Linglong Kong
    ,
    Bei Jiang
    ,
    Xiaodong Yan
  39. 39
    Adversarial Training in High-Dimensional Regression: Generated Data and Neural Networks
    Yue Xing
  40. 40
    Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
    Fuqiang Liu
    ,
    Sicong Jiang
    ,
    Luis Miranda-Moreno
    ,
    Seongjin Choi
    ,
    Lijun Sun
  41. 41
    Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits
    Sreejeet Maity
    ,
    Aritra Mitra
  42. 42
    Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics
    Jarren Briscoe
    ,
    Garrett Kepler
    ,
    Daryl DeFord
    ,
    Assefaw H. Gebremedhin
  43. 43
    All models are wrong, some are useful: Model Selection with Limited Labels
    Patrik Okanovic
    ,
    Andreas Kirsch
    ,
    Jannes Kasper
    ,
    Torsten Hoefler
    ,
    Andreas Krause
    ,
    Nezihe Merve Gürel
  44. 44
    All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling
    Emanuele Marconato
    ,
    Sébastien Lachapelle
    ,
    Sebastian Weichwald
    ,
    Luigi Gresele
  45. 45
    AlleNoise - large-scale text classification benchmark dataset with real-world label noise
    Alicja Raczkowska
    ,
    Aleksandra Osowska-Kurczab
    ,
    Jacek Szczerbinski
    ,
    Kalina Jasinska-Kobus
    ,
    Klaudia Nazarko
  46. 46
    Almost linear time differentially private release of synthetic graphs
    Zongrui Zou
    ,
    Jingcheng Liu
    ,
    Jalaj Upadhyay
  47. 47
    Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
    Paul Edmund Chang
    ,
    Nasrulloh Ratu Bagus Satrio Loka
    ,
    Daolang Huang
    ,
    Ulpu Remes
    ,
    Samuel Kaski
    ,
    Luigi Acerbi
  48. 48
    An Adaptive Method for Weak Supervision with Drifting Data
    Alessio Mazzetto
    ,
    Reza Esfandiarpoor
    ,
    Akash Singirikonda
    ,
    Eli Upfal
    ,
    Stephen H. Bach
  49. 49
    An Empirical Bernstein Inequality for Dependent Data in Hilbert Spaces and Applications
    Erfan Mirzaei
    ,
    Andreas Maurer
    ,
    Vladimir R. Kostic
    ,
    Massimiliano Pontil
  50. 50
    An Iterative Algorithm for Rescaled Hyperbolic Functions Regression
    Yeqi Gao
    ,
    Zhao Song
    ,
    Junze Yin