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| 2025 | Enhanced Equilibria-Solving via Private Information Pre-Branch Structure in Adversarial Team Games. | Chen Qiu, Haobo Fu, Kai Li, Jiajia Zhang, Xuan Wang |
| 2025 | Multi-Label Bayesian Active Learning with Inter-Label Relationships. | Yuanyuan Qi, Jueqing Lu, Xiaohao Yang, Joanne Enticott, Lan Du |
| 2025 | Black-box Optimization with Unknown Constraints via Overparameterized Deep Neural Networks. | Dat Phan-Trong, Hung The Tran, Sunil Gupta |
| 2025 | Are You Doing Better Than Random Guessing? A Call for Using Negative Controls When Evaluating Causal Discovery Algorithms. | Anne Helby Petersen |
| 2025 | A Trust-Region Method for Graphical Stein Variational Inference. | Liam Pavlovic, David M. Rosen |
| 2025 | Probabilistic Graph Circuits: Deep Generative Models for Tractable Probabilistic Inference over Graphs. | Milan Papez, Martin Rektoris, Vclav Smdl, Toms Pevn |
| 2025 | Exploring Exploration in Bayesian Optimization. | Leonard Papenmeier, Nuojin Cheng, Stephen Becker, Luigi Nardi |
| 2025 | An Information-theoretic Perspective of Hierarchical Clustering on Graphs. | Yicheng Pan, Bingchen Fan, Pengyu Long, Feng Zheng |
| 2025 | Correlated Quantization for Faster Nonconvex Distributed Optimization. | Andrei Panferov, Yury Demidovich, Ahmad Rammal, Peter Richtrik |
| 2025 | Concept Forgetting via Label Annealing. | Subhodip Panda, Ananda Theertha Suresh, Atri Guha, Prathosh A. P. |
| 2025 | Probability-Raising Causality for Uncertain Parametric Markov Decision Processes with PAC Guarantees. | Ryohei Oura, Yuji Ito |
| 2025 | Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees. | Azim Ospanov, Farzan Farnia |
| 2025 | Discriminative ordering through ensemble consensus. | Louis Ohl, Fredrik Lindsten |
| 2025 | i | Xuying Ning, Wujiang Xu, Tianxin Wei, Xiaolei Liu |
| 2025 | Bayesian Optimization over Bounded Domains with the Beta Product Kernel. | Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin |
| 2025 | Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization. | Dai Hai Nguyen, Hiroshi Mamitsuka, Atsuyoshi Nakamura |
| 2025 | Stochastic Embeddings : A Probabilistic and Geometric Analysis of Out-of-Distribution Behavior. | Anthony Nguyen, Emanuel Aldea, Sylvie Le Hgarat-Mascle, Renaud Lustrat |
| 2025 | Temperature Optimization for Bayesian Deep Learning. | Kenyon Ng, Chris van der Heide, Liam Hodgkinson, Susan Wei |
| 2025 | Relational Causal Discovery with Latent Confounders. | Matteo Negro, Andrea Piras, Ragib Ahsan, David Arbour, Elena Zheleva |
| 2025 | When Extragradient Meets PAGE: Bridging Two Giants to Boost Variational Inequalities. | Gleb Molodtsov, Valery Parfenov, Egor Petrov, Grigoriy Evseev, Daniil Medyakov, Aleksandr Beznosikov |
| 2025 | SpinSVAR: Estimating Structural Vector Autoregression Assuming Sparse Input. | Panagiotis Misiakos, Markus Pschel |
| 2025 | ODD: Overlap-aware Estimation of Model Performance under Distribution Shift. | Aayush Mishra, Anqi Liu |
| 2025 | Federated Rnyi Fair Inference in Federated Heterogeneous System. | Zhiyong Ma, Yuanjie Shi, Yan Yan, Jian Chen |
| 2025 | A Quantum Information Theoretic Approach to Tractable Probabilistic Models. | Pedro Zuidberg Dos Martires |