Papers
Pruning Filter in Filter
Fanxu Meng, Hao Cheng, Ke Li et al.
Pruning neural networks without any data by iteratively conserving synaptic flow
Hidenori Tanaka, Daniel Kunin, Daniel L Yamins et al.
Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point
Bita Darvish Rouhani, Daniel Lo, Ritchie Zhao et al.
PyGlove: Symbolic Programming for Automated Machine Learning
Daiyi Peng, Xuanyi Dong, Esteban Real et al.
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning
Iro Laina, Ruth Fong, Andrea Vedaldi
Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of Dimensionality
Nian Si, Jose Blanchet, Soumyadip Ghosh et al.
Quantile Propagation for Wasserstein-Approximate Gaussian Processes
Rui Zhang, Christian Walder, Edwin V. Bonilla et al.
Quantitative Propagation of Chaos for SGD in Wide Neural Networks
Valentin De Bortoli, Alain Durmus, Xavier Fontaine et al.
Quantized Variational Inference
Amir Dib
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space
Ekin Dogus Cubuk, Barret Zoph, Jon Shlens et al.
Randomized tests for high-dimensional regression: A more efficient and powerful solution
Yue Li, Ilmun Kim, Yuting Wei
Random Reshuffling is Not Always Better
Christopher M De Sa
Random Reshuffling: Simple Analysis with Vast Improvements
Konstantin Mishchenko, Ahmed Khaled, Peter Richtarik
Random Walk Graph Neural Networks
Giannis Nikolentzos, Michalis Vazirgiannis
RANet: Region Attention Network for Semantic Segmentation
Dingguo Shen, Yuanfeng Ji, Ping Li et al.
Rankmax: An Adaptive Projection Alternative to the Softmax Function
Weiwei Kong, Walid Krichene, Nicolas Mayoraz et al.
Rational neural networks
Nicolas Boulle, Yuji Nakatsukasa, Alex Townsend
Ratio Trace Formulation of Wasserstein Discriminant Analysis
Hexuan Liu, Yunfeng Cai, You-Lin Chen et al.
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning
Riccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov et al.
RD$^2$: Reward Decomposition with Representation Decomposition
Zichuan Lin, Derek Yang, Li Zhao et al.
Real World Games Look Like Spinning Tops
Wojciech M. Czarnecki, Gauthier Gidel, Brendan Tracey et al.
Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial Forms.
Sriram Sankaranarayanan, Yi Chou, Eric Goubault et al.
Reciprocal Adversarial Learning via Characteristic Functions
Shengxi Li, Zeyang Yu, Min Xiang et al.
Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
Zhiyuan Li, Kaifeng Lyu, Sanjeev Arora
Reconsidering Generative Objectives For Counterfactual Reasoning
Danni Lu, Chenyang Tao, Junya Chen et al.