Papers
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization
Yair Carmon, Arun Jambulapati, Yujia Jin et al.
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Daniel Kramer, Philine L Bommer, Carlo Tombolini et al.
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs
Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks
Litian Liang, Yaosheng Xu, Stephen Mcaleer et al.
Re-evaluating Word Mover’s Distance
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models
Tudor Manole, Nhat Ho
Region-Based Semantic Factorization in GANs
Jiapeng Zhu, Yujun Shen, Yinghao Xu et al.
Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation
Daniel Vial, Advait Parulekar, Sanjay Shakkottai et al.
Regret Minimization with Performative Feedback
Meena Jagadeesan, Tijana Zrnic, Celestine Mendler-Dünner
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning
Shentao Yang, Yihao Feng, Shujian Zhang et al.
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency
Qi Cai, Zhuoran Yang, Zhaoran Wang
Reinforcement Learning with Action-Free Pre-Training from Videos
Younggyo Seo, Kimin Lee, Stephen L James et al.
Removing Batch Normalization Boosts Adversarial Training
Haotao Wang, Aston Zhang, Shuai Zheng et al.
Representation Topology Divergence: A Method for Comparing Neural Network Representations.
Serguei Barannikov, Ilya Trofimov, Nikita Balabin et al.
Residual-Based Sampling for Online Outlier-Robust PCA
Tianhao Zhu, Jie Shen
Resilient and Communication Efficient Learning for Heterogeneous Federated Systems
Zhuangdi Zhu, Junyuan Hong, Steve Drew et al.
Rethinking Attention-Model Explainability through Faithfulness Violation Test
Yibing Liu, Haoliang Li, Yangyang Guo et al.
Rethinking Fano’s Inequality in Ensemble Learning
Terufumi Morishita, Gaku Morio, Shota Horiguchi et al.
Rethinking Graph Neural Networks for Anomaly Detection
Jianheng Tang, Jiajin Li, Ziqi Gao et al.
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems
Yue Gao, Ilia Shumailov, Kassem Fawaz
Retrieval-Augmented Reinforcement Learning
Anirudh Goyal, Abram Friesen, Andrea Banino et al.
RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval
Yihan Wu, Hongyang Zhang, Heng Huang
Retroformer: Pushing the Limits of End-to-end Retrosynthesis Transformer
Yue Wan, Chang-Yu Hsieh, Ben Liao et al.
Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees
Darshan Thaker, Paris Giampouras, Rene Vidal