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 |
|---|---|---|
| 2025 | Inverse Optimization with Prediction Market: A Characterization of Scoring Rules for Elciting System States. | Han Bao, Shinsaku Sakaue |
| 2025 | Calm Composite Losses: Being Improper Yet Proper Composite. | Han Bao, Nontawat Charoenphakdee |
| 2025 | Loss Gradient Gaussian Width based Generalization and Optimization Guarantees. | Arindam Banerjee, Qiaobo Li, Yingxue Zhou |
| 2025 | Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging. | Amartya Banerjee, Harlin Lee, Nir Sharon, Caroline Moosmller |
| 2025 | Minimum Empirical Divergence for Sub-Gaussian Linear Bandits. | Kapilan Balagopalan, Kwang-Sung Jun |
| 2025 | Score matching for bridges without learning time-reversals. | Elizabeth Louise Baker, Moritz Schauer, Stefan Sommer |
| 2025 | Theory of Agreement-on-the-Line in Linear Models and Gaussian Data. | Christina Baek, Aditi Raghunathan, J. Zico Kolter |
| 2025 | A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage. | Franois Bachoc, Tommaso Cesari, Roberto Colomboni |
| 2025 | The Sample Complexity of Stackelberg Games. | Francesco Bacchiocchi, Matteo Bollini, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti |
| 2025 | Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach. | Dheeraj Baby, Boran Han, Shuai Zhang, Cuixiong Hu, Bernie Wang, Yuxiang Wang |
| 2025 | Unbiased Quantization of the L | Nithish Suresh Babu, Ritesh Kumar, Shashank Vatedka |
| 2025 | Scalable Implicit Graphon Learning. | Ali Azizpour, Nicolas Zilberstein, Santiago Segarra |
| 2025 | Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership Leakage. | Achraf Azize, Debabrota Basu |
| 2025 | MEDUSA: Medical Data Under Shadow Attacks via Hybrid Model Inversion. | Asfandyar Azhar, Paul Thielen, Curtis P. Langlotz |
| 2025 | Model selection for behavioral learning data and applications to contextual bandits. | Julien Aubert, Louis Khler, Luc Lehricy, Giulia Mezzadri, Patricia Reynaud-Bouret |
| 2025 | Federated Communication-Efficient Multi-Objective Optimization. | Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong |
| 2025 | Fast Convergence of Softmax Policy Mirror Ascent. | Reza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani |
| 2025 | SINE: Scalable MPE Inference for Probabilistic Graphical Models using Advanced Neural Embeddings. | Shivvrat Arya, Tahrima Rahman, Vibhav Gogate |
| 2025 | High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise. | Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar |
| 2025 | ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. | Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Senetaire, Ali Caner Trkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram |
| 2025 | Bayesian Off-Policy Evaluation and Learning for Large Action Spaces. | Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba |
| 2025 | When the Universe is Too Big: Bounding Consideration Probabilities for Plackett-Luce Rankings. | Ben Aoki-Sherwood, Catherine Bregou, David Liben-Nowell, Kiran Tomlinson, Thomas Zeng |
| 2025 | The Strong Product Model for Network Inference without Independence Assumptions. | Bailey Andrew, David R. Westhead, Luisa Cutillo |
| 2025 | Noise-Aware Differentially Private Variational Inference. | Talal Alrawajfeh, Joonas Jlk, Antti Honkela |
| 2025 | M | Sarah Alnegheimish, Zelin He, Matthew Reimherr, Akash Chandrayan, Abhinav Pradhan, Luca D'Angelo |
551–575 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)