Papers
Fooling Neural Network Interpretations via Adversarial Model Manipulation
Juyeon Heo, Sunghwan Joo, Taesup Moon
Foundations of Comparison-Based Hierarchical Clustering
Debarghya Ghoshdastidar, Michaël Perrot, Ulrike von Luxburg
FreeAnchor: Learning to Match Anchors for Visual Object Detection
Xiaosong Zhang, Fang Wan, Chang Liu et al.
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
Krzysztof M Choromanski, Aldo Pacchiano, Jack Parker-Holder et al.
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan et al.
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Roman Beliy, Guy Gaziv, Assaf Hoogi et al.
Full-Gradient Representation for Neural Network Visualization
Suraj Srinivas, François Fleuret
Fully Dynamic Consistent Facility Location
Vincent Cohen-Addad, Niklas Oskar D Hjuler, Nikos Parotsidis et al.
Fully Neural Network based Model for General Temporal Point Processes
Takahiro Omi, naonori ueda, Kazuyuki Aihara
Fully Parameterized Quantile Function for Distributional Reinforcement Learning
Derek Yang, Li Zhao, Zichuan Lin et al.
Functional Adversarial Attacks
Cassidy Laidlaw, Soheil Feizi
Function-Space Distributions over Kernels
Gregory Benton, Wesley J Maddox, Jayson Salkey et al.
G2SAT: Learning to Generate SAT Formulas
Jiaxuan You, Haoze Wu, Clark Barrett et al.
Game Design for Eliciting Distinguishable Behavior
Fan Yang, Liu Leqi, Yifan Wu et al.
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks
Zhonghui You, Kun Yan, Jinmian Ye et al.
Gaussian-Based Pooling for Convolutional Neural Networks
Takumi Kobayashi
General E(2)-Equivariant Steerable CNNs
Maurice Weiler, Gabriele Cesa
Generalization Bounds for Neural Networks via Approximate Description Length
Amit Daniely, Elad Granot
Generalization Bounds in the Predict-then-Optimize Framework
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas et al.
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
Yuan Cao, Quanquan Gu
Generalization Error Analysis of Quantized Compressive Learning
Xiaoyun Li, Ping Li
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection
Bingzhe Wu, Shiwan Zhao, Chaochao Chen et al.
Generalization in multitask deep neural classifiers: a statistical physics approach
Anthony Ndirango, Tyler Lee
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li et al.
Generalization of Reinforcement Learners with Working and Episodic Memory
Meire Fortunato, Melissa Tan, Ryan Faulkner et al.