Papers
Recovery of sparse linear classifiers from mixture of responses
Venkata Gandikota, Arya Mazumdar, Soumyabrata Pal
Recurrent Quantum Neural Networks
Johannes Bausch
Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations
Joshua Glaser, Matthew Whiteway, John P. Cunningham et al.
Recursive Inference for Variational Autoencoders
Minyoung Kim, Vladimir Pavlovic
Reducing Adversarially Robust Learning to Non-Robust PAC Learning
Omar Montasser, Steve Hanneke, Nati Srebro
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
Ben Letham, Roberto Calandra, Akshara Rai et al.
Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals
Tongzhou Mu, Jiayuan Gu, Zhiwei Jia et al.
Regression with reject option and application to kNN
Ahmed Zaoui, Christophe Denis, Mohamed Hebiri
Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses
Yihan Zhou, Victor Sanches Portella, Mark Schmidt et al.
Regret in Online Recommendation Systems
Kaito Ariu, Narae Ryu, Se-Young Yun et al.
Regularized linear autoencoders recover the principal components, eventually
Xuchan Bao, James Lucas, Sushant Sachdeva et al.
Regularizing Black-box Models for Improved Interpretability
Gregory Plumb, Maruan Al-Shedivat, Ángel Alexander Cabrera et al.
Regularizing Towards Permutation Invariance In Recurrent Models
Edo Cohen-Karlik, Avichai Ben David, Amir Globerson
Reinforced Molecular Optimization with Neighborhood-Controlled Grammars
Chencheng Xu, Qiao Liu, Minlie Huang et al.
Reinforcement Learning for Control with Multiple Frequencies
Jongmin Lee, Byung-Jun Lee, Kee-Eung Kim
Reinforcement Learning with Augmented Data
Misha Laskin, Kimin Lee, Adam Stooke et al.
Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing
Arthur Delarue, Ross Anderson, Christian Tjandraatmadja
Reinforcement Learning with Feedback Graphs
Christoph Dann, Yishay Mansour, Mehryar Mohri et al.
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
Ruosong Wang, Ruslan Salakhutdinov, Lin Yang
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D
Ankit Goyal, Kaiyu Yang, Dawei Yang et al.
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces
Sebastien Ehrhardt, Oliver Groth, Aron Monszpart et al.
RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
Cheng Chi, Fangyun Wei, Han Hu
Relative gradient optimization of the Jacobian term in unsupervised deep learning
Luigi Gresele, Giancarlo Fissore, Adrián Javaloy et al.
Reliable Graph Neural Networks via Robust Aggregation
Simon Geisler, Daniel Zügner, Stephan Günnemann