| 2024 | Quantifying Local Model Validity using Active Learning. | Sven Lmmle, Can Bogoclu, Robert Vosshall, Anselm Haselhoff, Dirk Roos |
| 2024 | DataSP: A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with Context. | Alan A. Lahoud, Erik Schaffernicht, Johannes A. Stork |
| 2024 | Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action Abstraction. | Yunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang |
| 2024 | Optimization Framework for Semi-supervised Attributed Graph Coarsening. | Manoj Kumar, Subhanu Halder, Archit Kane, Ruchir Gupta, Sandeep Kumar |
| 2024 | Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions. | Patrick K. Kuiper, Ali Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose H. Blanchet, Vahid Tarokh |
| 2024 | How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression. | Lucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rgamer |
| 2024 | ILP-FORMER: Solving Integer Linear Programming with Sequence to Multi-Label Learning. | Shufeng Kong, Caihua Liu, Carla Gomes |
| 2024 | Causal Discovery with Deductive Reasoning: One Less Problem. | Jonghwan Kim, Inwoo Hwang, Sanghack Lee |
| 2024 | Active Learning Framework for Incomplete Networks. | Tung Khong, Cong Tran, Cuong Pham |
| 2024 | Targeted Reduction of Causal Models. | Armin Kekic, Bernhard Schlkopf, Michel Besserve |
| 2024 | Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable. | Yuta Kawakami, Manabu Kuroki, Jin Tian |
| 2024 | Probabilities of Causation for Continuous and Vector Variables. | Yuta Kawakami, Manabu Kuroki, Jin Tian |
| 2024 | Towards Scalable Bayesian Transformers: Investigating stochastic subset selection for NLP. | Peter Johannes Tejlgaard Kampen, Gustav Ragnar Stoettrup Als, Michael Riis Andersen |
| 2024 | Adaptive Softmax Trees for Many-Class Classification. | Rasul Kairgeldin, Magzhan Gabidolla, Miguel . Carreira-Perpin |
| 2024 | On the Convergence of Hierarchical Federated Learning with Partial Worker Participation. | Xiaohan Jiang, Hongbin Zhu |
| 2024 | Early-Exit Neural Networks with Nested Prediction Sets. | Metod Jazbec, Patrick Forr, Stephan Mandt, Dan Zhang, Eric T. Nalisnick |
| 2024 | Equilibrium Computation in Multidimensional Congestion Games: CSP and Learning Dynamics Approaches. | Mohammad T. Irfan, Hau Chan, Jared Soundy |
| 2024 | Revisiting Convergence of AdaGrad with Relaxed Assumptions. | Yusu Hong, Junhong Lin |
| 2024 | Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives. | Qi Heng Ho, Martin S. Feather, Federico Rossi, Zachary Sunberg, Morteza Lahijanian |
| 2024 | A Global Markov Property for Solutions of Stochastic Difference Equations and the corresponding Full Time Graphs. | Tom Hochsprung, Jakob Runge, Andreas Gerhardus |
| 2024 | Recursively-Constrained Partially Observable Markov Decision Processes. | Qi Heng Ho, Tyler J. Becker, Benjamin Kraske, Zakariya Laouar, Martin S. Feather, Federico Rossi, Morteza Lahijanian, Zachary Sunberg |
| 2024 | Quantum Kernelized Bandits. | Yasunari Hikima, Kazunori Murao, Sho Takemori, Yuhei Umeda |
| 2024 | Neural Active Learning Meets the Partial Monitoring Framework. | Maxime Heuillet, Ola Ahmad, Audrey Durand |
| 2024 | On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots. | Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan |
| 2024 | Adjustment Identification Distance: A gadjid for Causal Structure Learning. | Leonard Henckel, Theo Wrtzen, Sebastian Weichwald |