International Conference on Artificial Intelligence and Statistics
AISTATS
A
CORE rank
CORE rank (raw)
A
Acceptance rate
27.6% (2024)
Fields of research
Machine Learning · Artificial Intelligence
Papers indexed
4,516
1995–2025
Papers per year
1995583 peak2025
Most published authors
AISTATS papers
4,516 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2021 | On the Linear Convergence of Policy Gradient Methods for Finite MDPs. | Jalaj Bhandari, Daniel Russo |
| 2021 | Anderson acceleration of coordinate descent. | Quentin Bertrand, Mathurin Massias |
| 2021 | Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders. | Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi |
| 2021 | Interpretable Random Forests via Rule Extraction. | Clment Bnard, Grard Biau, Sbastien Da Veiga, Erwan Scornet |
| 2021 | Optimizing Percentile Criterion using Robust MDPs. | Bahram Behzadian, Reazul Hasan Russel, Marek Petrik, Chin Pang Ho |
| 2021 | Understanding and Mitigating Exploding Inverses in Invertible Neural Networks. | Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jrn-Henrik Jacobsen |
| 2021 | Gaming Helps! Learning from Strategic Interactions in Natural Dynamics. | Yahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani |
| 2021 | Logistic Q-Learning. | Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu |
| 2021 | Implicit Regularization via Neural Feature Alignment. | Aristide Baratin, Thomas George, Csar Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien |
| 2021 | One-Round Communication Efficient Distributed M-Estimation. | Yajie Bao, Weijia Xiong |
| 2021 | The Sample Complexity of Level Set Approximation. | Franois Bachoc, Tommaso Cesari, Sbastien Gerchinovitz |
| 2021 | An Optimal Reduction of TV-Denoising to Adaptive Online Learning. | Dheeraj Baby, Xuandong Zhao, Yu-Xiang Wang |
| 2021 | Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications. | Guillaume Ausset, Stphan Clmenon, Franois Portier |
| 2021 | Counterfactual Representation Learning with Balancing Weights. | Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin |
| 2021 | Bandit algorithms: Letting go of logarithmic regret for statistical robustness. | Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna P. Jagannathan |
| 2021 | Geometrically Enriched Latent Spaces. | Georgios Arvanitidis, Sren Hauberg, Bernhard Schlkopf |
| 2021 | Corralling Stochastic Bandit Algorithms. | Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri |
| 2021 | When MAML Can Adapt Fast and How to Assist When It Cannot. | Sbastien M. R. Arnold, Shariq Iqbal, Fei Sha |
| 2021 | Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems. | Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao |
| 2021 | Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling. | Setareh Ariafar, Zelda Mariet, Dana H. Brooks, Jennifer G. Dy, Jasper Snoek |
| 2021 | Efficient Balanced Treatment Assignments for Experimentation. | David Arbour, Drew Dimmery, Anup B. Rao |
| 2021 | Direct-Search for a Class of Stochastic Min-Max Problems. | Sotirios-Konstantinos Anagnostidis, Aurlien Lucchi, Youssef Diouane |
| 2021 | Robust Learning under Strong Noise via SQs. | Ioannis Anagnostides, Themis Gouleakis, Ali Marashian |
| 2021 | Automatic structured variational inference. | Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven |
| 2021 | Momentum Improves Optimization on Riemannian Manifolds. | Foivos Alimisis, Antonio Orvieto, Gary Bcigneul, Aurlien Lucchi |
2,526–2,550 of 4,516← PreviousNext →
Comparable venues
Other A*/A conferences filed under the same field of research.
- A*ICMLInternational Conference on Machine Learning
- A*ICLRInternational Conference on Learning Representations
- A*COLTConference on Learning Theory
- APPSNParallel Problem Solving from Nature
- AECML PKDDEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008)
- A*NeurIPSAdvances in Neural Information Processing Systems (was NIPS)