| 2025 | A Shapley-value Guided Rationale Editor for Rationale Learning. | Zixin Kuang, Meng-Fen Chiang, Wang-Chien Lee |
| 2025 | Change Point Detection in Hadamard Spaces by Alternating Minimization. | Anica Kostic, Vincent Runge, Charles Truong |
| 2025 | Disentangling Interactions and Dependencies in Feature Attributions. | Gunnar Knig, Eric Gnther, Ulrike von Luxburg |
| 2025 | Common Learning Constraints Alter Interpretations of Direct Preference Optimization. | Lemin Kong, Xiangkun Hu, Tong He, David Wipf |
| 2025 | Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints. | Lingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M. Ferber, Yian Ma, Carla P. Gomes, Chao Zhang |
| 2025 | Bandit Pareto Set Identification in a Multi-Output Linear Model. | Cyrille Kone, Emilie Kaufmann, Laura Richert |
| 2025 | Pareto Set Identification With Posterior Sampling. | Cyrille Kone, Marc Jourdan, Emilie Kaufmann |
| 2025 | Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention. | Alexander Koebler, Thomas Decker, Ingo Thon, Volker Tresp, Florian Buettner |
| 2025 | Domain Adaptation and Entanglement: an Optimal Transport Perspective. | Okan Koc, Alexander Soen, Chao-Kai Chiang, Masashi Sugiyama |
| 2025 | Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions. | Omer Noy Klein, Alihan Hyk, Ron Shamir, Uri Shalit, Mihaela van der Schaar |
| 2025 | Deep Generative Quantile Bayes. | Jungeum Kim, Percy S. Zhai, Veronika Rockov |
| 2025 | Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds. | Masanari Kimura, Howard D. Bondell |
| 2025 | Robust Estimation in metric spaces: Achieving Exponential Concentration with a Frchet Median. | Jakwang Kim, Jiyoung Park, Anirban Bhattacharya |
| 2025 | Bayesian Principles Improve Prompt Learning In Vision-Language Models. | Mingyu Kim, Jongwoo Ko, Mijung Park |
| 2025 | A Computation-Efficient Method of Measuring Dataset Quality based on the Coverage of the Dataset. | Beomjun Kim, Jaehwan Kim, Kangyeon Kim, Sunwoo Kim, Heejin Ahn |
| 2025 | Learning the Pareto Front Using Bootstrapped Observation Samples. | Wonyoung Kim, Garud Iyengar, Assaf Zeevi |
| 2025 | Ant Colony Sampling with GFlowNets for Combinatorial Optimization. | Minsu Kim, Sanghyeok Choi, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio |
| 2025 | A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. | Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo vila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L. Borsa, Arthur Guez, Will Dabney |
| 2025 | Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis. | Rmi Khellaf, Aurlien Bellet, Julie Josse |
| 2025 | Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects. | Seyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi |
| 2025 | DPFL: Decentralized Personalized Federated Learning. | Salma Kharrat, Marco Canini, Samuel Horvth |
| 2025 | Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators. | Naichang Ke, Ryogo Tanaka, Yoshinobu Kawahara |
| 2025 | On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients. | Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad |
| 2025 | TempTest: Local Normalization Distortion and the Detection of Machine-generated Text. | Tom Kempton, Stuart Burrell, Connor Cheverall |
| 2025 | Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement Learning. | Aya Kayal, Sattar Vakili, Laura Toni, Alberto Bernacchia |