| 2025 | Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits. | Ha Manh Bui, Enrique Mallada, Anqi Liu |
| 2025 | Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics. | Jarren Briscoe, Garrett Kepler, Daryl DeFord, Assefaw H. Gebremedhin |
| 2025 | Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time. | Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang |
| 2025 | Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient Descent. | Guillaume Braun, Minh Ha Quang, Masaaki Imaizumi |
| 2025 | Learning the Distribution Map in Reverse Causal Performative Prediction. | Daniele Bracale, Subha Maity, Yuekai Sun, Moulinath Banerjee |
| 2025 | Microfoundation inference for strategic prediction. | Daniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun |
| 2025 | Density Ratio-based Proxy Causal Learning Without Density Ratios. | Bariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton |
| 2025 | Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoning. | Avinandan Bose, Laurent Lessard, Maryam Fazel, Krishnamurthy Dj Dvijotham |
| 2025 | Offline Multi-task Transfer RL with Representational Penalization. | Avinandan Bose, Simon Shaolei Du, Maryam Fazel |
| 2025 | A Novel Convex Gaussian Min Max Theorem for Repeated Features. | David Bosch, Ashkan Panahi |
| 2025 | Nonparametric estimation of Hawkes processes with RKHSs. | Anna Bonnet, Maxime Sangnier |
| 2025 | Automatically Adaptive Conformal Risk Control. | Vincent Blot, Anastasios Nikolas Angelopoulos, Michael I. Jordan, Nicolas J.-B. Brunel |
| 2025 | SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph Search. | Leonardo Martins Bianco, Christine Keribin, Zacharie Naulet |
| 2025 | Approximating the Total Variation Distance between Gaussians. | Arnab Bhattacharyya, Weiming Feng, Piyush Srivastava |
| 2025 | Learning High-dimensional Gaussians from Censored Data. | Arnab Bhattacharyya, Constantinos Daskalakis, Themis Gouleakis, Yuhao Wang |
| 2025 | Cost-aware simulation-based inference. | Ayush Bharti, Daolang Huang, Samuel Kaski, Franois-Xavier Briol |
| 2025 | Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion. | Grigor Bezirganyan, Sana Sellami, Laure Berti-quille, Sbastien Fournier |
| 2025 | Variational Inference on the Boolean Hypercube with the Quantum Entropy. | Eliot Beyler, Francis Bach |
| 2025 | Koopman-Equivariant Gaussian Processes. | Petar Bevanda, Max Beier, Alexandre Capone, Stefan Sosnowski, Sandra Hirche, Armin Lederer |
| 2025 | The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control. | Mathieu Besanon, Sebastian Pokutta, Elias Samuel Wirth |
| 2025 | Differentiable Causal Structure Learning with Identifiability by NOTIME. | Jeroen Berrevoets, Jakob Raymaekers, Mihaela van der Schaar, Tim Verdonck, Ruicong Yao |
| 2025 | On Tradeoffs in Learning-Augmented Algorithms. | Ziyad Benomar, Vianney Perchet |
| 2025 | Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses. | Mathieu Bazinet, Valentina Zantedeschi, Pascal Germain |
| 2025 | Approximate information maximization for bandit games. | Alex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson, Etienne Boursier |
| 2025 | Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps. | Ricardo Baptista, Aram-Alexandre Pooladian, Michael Brennan, Youssef Marzouk, Jonathan Niles-Weed |