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 |
|---|---|---|
| 2024 | Robust Sparse Voting. | Youssef Allouah, Rachid Guerraoui, L-Nguyn Hoang, Oscar Villemaud |
| 2024 | Pessimistic Off-Policy Multi-Objective Optimization. | Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu |
| 2024 | Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. | Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt |
| 2024 | Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints. | Ahmet Alacaoglu, Stephen J. Wright |
| 2024 | Multi-Domain Causal Representation Learning via Weak Distributional Invariances. | Kartik Ahuja, Amin Mansouri, Yixin Wang |
| 2024 | Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning. | Maheed H. Ahmed, Mahsa Ghasemi |
| 2024 | Agnostic Multi-Robust Learning using ERM. | Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M. Stangl |
| 2024 | Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio. | Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten |
| 2024 | Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels. | Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d'Alch-Buc |
| 2024 | Sharp error bounds for imbalanced classification: how many examples in the minority class? | Anass Aghbalou, Anne Sabourin, Franois Portier |
| 2024 | Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. | Arman Adibi, Nicol Dal Fabbro, Luca Schenato, Sanjeev R. Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra |
| 2024 | Looping in the Human: Collaborative and Explainable Bayesian Optimization. | Masaki Adachi, Brady Planden, David A. Howey, Michael A. Osborne, Sebastian Orbell, Natalia Ares, Krikamol Muandet, Siu Lun Chau |
| 2024 | Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. | Masaki Adachi, Satoshi Hayakawa, Martin Jrgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne |
| 2024 | Multitask Online Learning: Listen to the Neighborhood Buzz. | Juliette Achddou, Nicol Cesa-Bianchi, Pierre Laforgue |
| 2024 | Imposing Fairness Constraints in Synthetic Data Generation. | Mahed Abroshan, Andrew Elliott, Mohammad Mahdi Khalili |
| 2024 | Lexicographic Optimization: Algorithms and Stability. | Jacob D. Abernethy, Robert E. Schapire, Umar Syed |
| 2024 | On the Nystrm Approximation for Preconditioning in Kernel Machines. | Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher, Mikhail Belkin |
| 2024 | Enhancing In-context Learning via Linear Probe Calibration. | Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen |
| 2024 | TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular Generation. | Chen Li, Yoshihiro Yamanishi |
| 2024 | Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. | Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman |
| 2024 | BLIS-Net: Classifying and Analyzing Signals on Graphs. | Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter |
| 2024 | On Feynman-Kac training of partial Bayesian neural networks. | Zheng Zhao, Sebastian Mair, Thomas B. Schn, Jens Sjlund |
| 2024 | Self-Supervised Quantization-Aware Knowledge Distillation. | Kaiqi Zhao, Ming Zhao |
| 2024 | Solving Attention Kernel Regression Problem via Pre-conditioner. | Zhao Song, Junze Yin, Lichen Zhang |
| 2024 | Fast Dynamic Sampling for Determinantal Point Processes. | Zhao Song, Junze Yin, Lichen Zhang, Ruizhe Zhang |
1,101–1,125 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)