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20182021
most citedExtending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers

18 citations · 82 across the 15 of their papers we have counts for

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8 papers · 1 filter

cs.LG2021

One-shot Learning with Absolute Generalization

Hao Su

One-shot learning is proposed to make a pretrained classifier workable on a new dataset based on one labeled samples from each pattern. However, few of researchers consider whether…

cs.LG202117 cited

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics

Zhiao Huang, Yuanming Hu, Tao Du +4

Simulated virtual environments serve as one of the main driving forces behind developing and evaluating skill learning algorithms. However, existing environments typically only sim…

cs.LG20203 cited

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks

Hao Tang, Zhiao Huang, Jiayuan Gu +2

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Tak…

cs.LG201918 cited

State Alignment-based Imitation Learning

Fangchen Liu, Zhan Ling, Tongzhou Mu +1

Consider an imitation learning problem that the imitator and the expert have different dynamics models. Most of the current imitation learning methods fail because they focus on im…

cs.LG2019

Information-Theoretic Local Minima Characterization and Regularization

Zhiwei Jia, Hao Su

Recent advances in deep learning theory have evoked the study of generalizability across different local minima of deep neural networks (DNNs). While current work focused on either…

cs.LG2019

Mapping State Space using Landmarks for Universal Goal Reaching

Zhiao Huang, Fangchen Liu, Hao Su

An agent that has well understood the environment should be able to apply its skills for any given goals, leading to the fundamental problem of learning the Universal Value Functio…