International Conference on Artificial Intelligence and Statistics

AISTATS

CORE rank

CORE rank (raw)

Acceptance rate

27.6% (2024)

Fields of research

Machine Learning · Artificial Intelligence

Papers indexed

4,516

1995–2025

Best Artificial Intelligence conferences Best Machine Learning conferences

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
2019	A Fast Sampling Algorithm for Maximum Inner Product Search.	Qin Ding, Hsiang-Fu Yu, Cho-Jui Hsieh
2019	Bayesian Learning of Neural Network Architectures.	Georgi Dikov, Justin Bayer
2019	Interpretable Almost-Exact Matching for Causal Inference.	Awa Dieng, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
2019	Avoiding Latent Variable Collapse with Generative Skip Models.	Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei
2019	Attenuating Bias in Word vectors.	Sunipa Dev, Jeff M. Phillips
2019	On Euclidean k-Means Clustering with alpha-Center Proximity.	Amit Deshpande, Anand Louis, Apoorv Vikram Singh
2019	Correcting the bias in least squares regression with volume-rescaled sampling.	Michal Derezinski, Manfred K. Warmuth, Daniel Hsu
2019	Deep Switch Networks for Generating Discrete Data and Language.	Payam Delgosha, Naveen Goela
2019	Bridging the gap between regret minimization and best arm identification, with application to A/B tests.	Rmy Degenne, Thomas Nedelec, Clment Calauznes, Vianney Perchet
2019	Error bounds for sparse classifiers in high-dimensions.	Antoine Dedieu
2019	On Multi-Cause Approaches to Causal Inference with Unobserved Counfounding: Two Cautionary Failure Cases and A Promising Alternative.	Alexander D'Amour
2019	Kernel Exponential Family Estimation via Doubly Dual Embedding.	Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He
2019	Database Alignment with Gaussian Features.	Osman Emre Dai, Daniel Cullina, Negar Kiyavash
2019	Distilling Policy Distillation.	Wojciech M. Czarnecki, Razvan Pascanu, Simon Osindero, Siddhant M. Jayakumar, Grzegorz Swirszcz, Max Jaderberg
2019	SPONGE: A generalized eigenproblem for clustering signed networks.	Mihai Cucuringu, Peter Davies, Aldo Glielmo, Hemant Tyagi
2019	Provable Robustness of ReLU networks via Maximization of Linear Regions.	Francesco Croce, Maksym Andriushchenko, Matthias Hein
2019	Region-Based Active Learning.	Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang
2019	Learning Rules-First Classifiers.	Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan
2019	Interpretable Cascade Classifiers with Abstention.	Matthieu Clertant, Nataliya Sokolovska, Yann Chevaleyre, Blaise Hanczar
2019	Online Learning in Kernelized Markov Decision Processes.	Sayak Ray Chowdhury, Aditya Gopalan
2019	KAMA-NNs: Low-dimensional Rotation Based Neural Networks.	Krzysztof Choromanski, Aldo Pacchiano, Jeffrey Pennington, Yunhao Tang
2019	Large-Margin Classification in Hyperbolic Space.	Hyunghoon Cho, Benjamin Demeo, Jian Peng, Bonnie Berger
2019	Matroids, Matchings, and Fairness.	Flavio Chierichetti, Ravi Kumar, Silvio Lattanzi, Sergei Vassilvitskii
2019	HS	I (Eli) Chien, Huozhi Zhou, Pan Li
2019	A Thompson Sampling Algorithm for Cascading Bandits.	Wang Chi Cheung, Vincent Y. F. Tan, Zixin Zhong

3,276–3,300 of 4,516← Previous Next →

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