Papers
Improving Policy-Constrained Kidney Exchange via Pre-Screening
Duncan McElfresh, Michael Curry, Tuomas Sandholm et al.
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider, Evgenia Rusak, Luisa Eck et al.
Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms
Tengyu Xu, Zhe Wang, Yingbin Liang
Improving Sparse Vector Technique with Renyi Differential Privacy
Yuqing Zhu, Yu-Xiang Wang
Incorporating BERT into Parallel Sequence Decoding with Adapters
Junliang Guo, Zhirui Zhang, Linli Xu et al.
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
Wanqian Yang, Lars Lorch, Moritz Graule et al.
Incorporating Pragmatic Reasoning Communication into Emergent Language
Yipeng Kang, Tonghan Wang, Gerard de Melo
Independent Policy Gradient Methods for Competitive Reinforcement Learning
Constantinos Daskalakis, Dylan J Foster, Noah Golowich
Inductive Quantum Embedding
Santosh Kumar Srivastava, Dinesh Khandelwal, Dhiraj Madan et al.
Inference for Batched Bandits
Kelly Zhang, Lucas Janson, Susan Murphy
Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation
Jianfeng Zhang, Xuecheng Nie, Jiashi Feng
Inferring learning rules from animal decision-making
Zoe Ashwood, Nicholas A. Roy, Ji Hyun Bak et al.
Influence-Augmented Online Planning for Complex Environments
Jinke He, Miguel Suau de Castro, Frans Oliehoek
Information Maximization for Few-Shot Learning
Malik Boudiaf, Imtiaz Ziko, Jérôme Rony et al.
Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
Zifeng Wang, Xi Chen, Rui Wen et al.
Information theoretic limits of learning a sparse rule
Clément Luneau, jean barbier, Nicolas Macris
Information Theoretic Regret Bounds for Online Nonlinear Control
Sham Kakade, Akshay Krishnamurthy, Kendall Lowrey et al.
Information-theoretic Task Selection for Meta-Reinforcement Learning
Ricardo Luna Gutierrez, Matteo Leonetti
Input-Aware Dynamic Backdoor Attack
Tuan Anh Nguyen, Anh Tran
In search of robust measures of generalization
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal et al.
Instance Based Approximations to Profile Maximum Likelihood
Nima Anari, Moses Charikar, Kirankumar Shiragur et al.
Instance-based Generalization in Reinforcement Learning
Martin Bertran, Natalia Martinez, Mariano Phielipp et al.
Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms
Hilal Asi, John C. Duchi
Instance Selection for GANs
Terrance DeVries, Michal Drozdzal, Graham W. Taylor
Instance-wise Feature Grouping
Aria Masoomi, Chieh Wu, Tingting Zhao et al.