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AISTATS 2026 Conference Submissions

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Convergence of Projected Stochastic Natural Gradient Variational Inference for Various Step Size and Sample or Batch Size Schedules
Thomas Guilmeau, Hadrien Hendrikx, Florence Forbes
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Unsupervised Ensemble Learning Through Deep Energy-based Models
Ariel Maymon, Yanir Buznah, Uri Shaham
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Beyond Pooling: Matching for Robust Generalization Under Data Heterogeneity
Ayush Roy, Rudrasis Chakraborty, Lav R. Varshney, Vishnu Suresh Lokhande
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Counterfactual Credit Guided Bayesian Optimization
Qiyu Wei, Haowei Wang, Richard Allmendinger, Mauricio A Álvarez
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Tyler’s M-estimator Through the Lens of Convex-Concave Programming
Daniel Cederberg
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Spotlight
- Readers: Everyone
On the hardness of Reinforcement Learning with Transition Lookahead
Corentin Pla, Hugo Richard, Marc Abeille, Nadav Merlis, Vianney Perchet
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Probabilistic multi-dimensional classification with incomplete data at the prediction time
Thu Ha DO, Vu-Linh Nguyen, Yves Grandvalet
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to LLM Fine-Tuning
Sihan Zeng, Sujay Bhatt, Sumitra Ganesh, Alec Koppel
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Partially Lazy Gradient Descent for Smoothed Online Learning
Naram Mhaisen, George Iosifidis
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors
Julius Kobialka, Emanuel Sommer, Chris Kolb, Juntae Kwon, Daniel Dold, David Rügamer
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Spotlight
- Readers: Everyone
Rethinking Intrinsic Dimension Estimation in Neural Representations
Rickmer Schulte, David Rügamer
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent
Tobias Pielok, Bernd Bischl, David Rügamer
- Published: 03 Feb 2026, Last Modified: 02 May 2026
- AISTATS 2026 Poster
- Readers: Everyone

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