AISTATS 2025 Conference Submissions

Learning from biased positive-unlabeled data via threshold calibration
Paweł Teisseyre, Timo Martens, Jessa Bekker, Jesse Davis
- Published: 22 Jan 2025, Last Modified: 06 Mar 2025
- AISTATS 2025 Oral
- Readers: Everyone
Credibility-Aware Multimodal Fusion Using Probabilistic Circuits
Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan
- Published: 22 Jan 2025, Last Modified: 13 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation
Yilin Xie, Shiqiang Zhang, Joel Paulson, Calvin Tsay
- Published: 22 Jan 2025, Last Modified: 15 Apr 2025
- AISTATS 2025 Poster
- Readers: Everyone
A Subquadratic Time Approximation Algorithm for Individually Fair k-Center
Matthijs Ebbens, Nicole Funk, Jan Höckendorff, Christian Sohler, Vera Weil
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Distributional Adversarial Loss
Saba Ahmadi, Siddharth Bhandari, Avrim Blum, Chen Dan, Prabhav Jain
- Published: 22 Jan 2025, Last Modified: 22 Apr 2025
- AISTATS 2025 Poster
- Readers: Everyone
Efficient Exploitation of Hierarchical Structure in Sparse Reward Reinforcement Learning
Gianluca Drappo, Arnaud Robert, Marcello Restelli, Aldo A. Faisal, Alberto Maria Metelli, Ciara Pike-Burke
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging
Amartya Banerjee, Harlin Lee, Nir Sharon, Caroline Moosmüller
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits
Brian M Cho, Dominik Meier, Kyra Gan, Nathan Kallus
- Published: 22 Jan 2025, Last Modified: 11 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables
Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Henri Joseph Senetaire, Ali Caner Turkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram
- Published: 22 Jan 2025, Last Modified: 24 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Best-Arm Identification in Unimodal Bandits
Riccardo Poiani, Marc Jourdan, Emilie Kaufmann, Rémy Degenne
- Published: 22 Jan 2025, Last Modified: 11 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue Lu, Bruno Loureiro
- Published: 22 Jan 2025, Last Modified: 11 Mar 2025
- AISTATS 2025 Oral
- Readers: Everyone
Common Learning Constraints Alter Interpretations of Direct Preference Optimization
Lemin Kong, Xiangkun Hu, Tong He, David Wipf
- Published: 22 Jan 2025, Last Modified: 11 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Information-Theoretic Measures on Lattices for Higher-Order Interactions
Zhaolu Liu, Mauricio Barahona, Robert Peach
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Legitimate ground-truth-free metrics for deep uncertainty classification scoring
Arthur Pignet, Chiara Regniez, John Klein
- Published: 22 Jan 2025, Last Modified: 06 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
Alexander Koebler, Thomas Decker, Ingo Thon, Volker Tresp, Florian Buettner
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Classification of High-dimensional Time Series in Spectral Domain Using Explainable Features with Applications to Neuroimaging Data
Sarbojit Roy, Malik Shahid Sultan, Tania Reyes Vallejo, Leena Ali Ibrahim, Hernando Ombao
- Published: 22 Jan 2025, Last Modified: 22 Apr 2025
- AISTATS 2025 Poster
- Readers: Everyone
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation
Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf
- Published: 22 Jan 2025, Last Modified: 08 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Tensor Network-Constrained Kernel Machines as Gaussian Processes
Frederiek Wesel, kim batselier
- Published: 22 Jan 2025, Last Modified: 25 Feb 2025
- AISTATS 2025 Poster
- Readers: Everyone
Generalization Bounds for Dependent Data using Online-to-Batch Conversion.
Sagnik Chatterjee, MANUJ MUKHERJEE, Alhad Sethi
- Published: 22 Jan 2025, Last Modified: 06 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
A Causal Framework for Evaluating Deferring Systems
Filippo Palomba, Andrea Pugnana, Jose Manuel Alvarez, Salvatore Ruggieri
- Published: 22 Jan 2025, Last Modified: 06 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Disentangling Interactions and Dependencies in Feature Attributions
Gunnar König, Eric Günther, Ulrike von Luxburg
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability
Zhuorui Ye, Farzan Farnia
- Published: 22 Jan 2025, Last Modified: 11 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csáji
- Published: 22 Jan 2025, Last Modified: 10 Mar 2025
- AISTATS 2025 Poster
- Readers: Everyone
Towards Fair Graph Learning without Demographic Information
Zichong Wang, Nhat Hoang, Xingyu Zhang, Kevin Bello, Xiangliang Zhang, Sundararaja Sitharama Iyengar, Wenbin Zhang
- Published: 22 Jan 2025, Last Modified: 15 Apr 2025
- AISTATS 2025 Poster
- Readers: Everyone
Calibrated Computation-Aware Gaussian Processes
Disha Hegde, Mohamed Adil, Jon Cockayne
- Published: 22 Jan 2025, Last Modified: 15 Apr 2025
- AISTATS 2025 Poster
- Readers: Everyone