Papers
ReSSL: Relational Self-Supervised Learning with Weak Augmentation
Mingkai Zheng, Shan You, Fei Wang et al.
ResT: An Efficient Transformer for Visual Recognition
Qinglong Zhang, Yu-Bin Yang
Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization
Guoqiang Wu, Chongxuan LI, Kun Xu et al.
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence
Deng-Bao Wang, Lei Feng, Min-Ling Zhang
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds
Sameera Ramasinghe, Moshiur Farazi, Salman H Khan et al.
Rethinking gradient sparsification as total error minimization
Atal Sahu, Aritra Dutta, Ahmed M. Abdelmoniem et al.
Rethinking Graph Transformers with Spectral Attention
Devin Kreuzer, Dominique Beaini, Will Hamilton et al.
Rethinking Neural Operations for Diverse Tasks
Nicholas Roberts, Mikhail Khodak, Tri Dao et al.
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang
Rethinking the Pruning Criteria for Convolutional Neural Network
Zhongzhan Huang, Wenqi Shao, Xinjiang Wang et al.
Rethinking the Variational Interpretation of Accelerated Optimization Methods
Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand
Retiring Adult: New Datasets for Fair Machine Learning
Frances Ding, Moritz Hardt, John P. Miller et al.
RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
Krishnateja Killamsetty, Xujiang Zhao, Feng Chen et al.
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes
Jai Moondra, Hassan Mortagy, Swati Gupta
Revealing and Protecting Labels in Distributed Training
Trung Dang, Om Thakkar, Swaroop Ramaswamy et al.
Revenue maximization via machine learning with noisy data
Ellen Vitercik, Tom Yan
Reverse-Complement Equivariant Networks for DNA Sequences
Vincent Mallet, Jean-Philippe Vert
Reverse engineering learned optimizers reveals known and novel mechanisms
Niru Maheswaranathan, David Sussillo, Luke Metz et al.
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems
Jimmy Smith, Scott Linderman, David Sussillo
Revisiting 3D Object Detection From an Egocentric Perspective
Boyang Deng, Charles R Qi, Mahyar Najibi et al.
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis et al.
Revisiting Deep Learning Models for Tabular Data
Yury Gorishniy, Ivan Rubachev, Valentin Khrulkov et al.
Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme
Shaojie Li, Jie Wu, Xuefeng Xiao et al.
Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness
Zifeng Wang, Tong Jian, Aria Masoomi et al.
Revisiting Model Stitching to Compare Neural Representations
Yamini Bansal, Preetum Nakkiran, Boaz Barak