Papers
8,340 papers found
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
Rui Xue, Haoyu Han, Mohamadali Torkamani et al.
LeadFL: Client Self-Defense against Model Poisoning in Federated Learning
Chaoyi Zhu, Stefanie Roos, Lydia Y. Chen
Learnability and Algorithm for Continual Learning
Gyuhak Kim, Changnan Xiao, Tatsuya Konishi et al.
Learning Affinity with Hyperbolic Representation for Spatial Propagation
Jin-Hwi Park, Jaesung Choe, Inhwan Bae et al.
Learning Antidote Data to Individual Unfairness
Peizhao Li, Ethan Xia, Hongfu Liu
Learning-augmented private algorithms for multiple quantile release
Mikhail Khodak, Kareem Amin, Travis Dick et al.
Learning Belief Representations for Partially Observable Deep RL
Andrew Wang, Andrew C Li, Toryn Q. Klassen et al.
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
Youwei Liang, Kevin Stone, Ali Shameli et al.
Learning Control by Iterative Inversion
Gal Leibovich, Guy Jacob, Or Avner et al.
Learning Controllable Degradation for Real-World Super-Resolution via Constrained Flows
Seobin Park, Dongjin Kim, Sungyong Baik et al.
Learning Control-Oriented Dynamical Structure from Data
Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan et al.
Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic
Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi et al.
Learning Deep Time-index Models for Time Series Forecasting
Gerald Woo, Chenghao Liu, Doyen Sahoo et al.
Learning Dense Correspondences between Photos and Sketches
Xuanchen Lu, Xiaolong Wang, Judith E Fan
Learning Distributions over Quantum Measurement Outcomes
Weiyuan Gong, Scott Aaronson
Learning Dynamic Query Combinations for Transformer-based Object Detection and Segmentation
Yiming Cui, Linjie Yang, Haichao Yu
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks
Dominik Schnaus, Jongseok Lee, Daniel Cremers et al.
Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees
Pengfei Li, Jianyi Yang, Shaolei Ren
Learning Functional Distributions with Private Labels
Changlong Wu, Yifan Wang, Ananth Grama et al.
Learning GFlowNets From Partial Episodes For Improved Convergence And Stability
Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov et al.
Learning Globally Smooth Functions on Manifolds
Juan Cervino, Luiz F. O. Chamon, Benjamin David Haeffele et al.
Learning Hidden Markov Models When the Locations of Missing Observations are Unknown
Binyamin Perets, Mark Kozdoba, Shie Mannor
Learning in POMDPs is Sample-Efficient with Hindsight Observability
Jonathan Lee, Alekh Agarwal, Christoph Dann et al.
Learning Instance-Specific Augmentations by Capturing Local Invariances
Ning Miao, Tom Rainforth, Emile Mathieu et al.
Learning Intuitive Policies Using Action Features
Mingwei Ma, Jizhou Liu, Samuel Sokota et al.