Country
Constructing Fast Network through Deconstruction of Convolution
Neural Information Processing Systems http://nips.cc/
Unsupervised Video Object Segmentation for Deep Reinforcement Learning
Vikash Goel, Jameson Weng, Pascal Poupart
Neural Information Processing Systems http://nips.cc/
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning
Wenjie Shi, Shiji Song, Hui Wu, Ya-Chu Hsu, Cheng Wu, Gao Huang
Model-free deepreinforcement learning (RL)algorithms havebeenwidely used for a range of complex control tasks.
HIQL: Offline Goal-Conditioned RL with Latent States as Actions Seohong Park
We observe that part of this difficulty stems from the "signal-to-noise"
Provably Powerful Graph Networks
Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, Yaron Lipman
Graphs are an important data modality which is frequently used in many fields of science and engineering.
Bilinear Attention Networks
Jin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang
A man in a denim shirt and pants is smoking a cigarette while playing a cello for money.(c)
An Efficient Pruning Algorithm for Robust Isotonic Regression
Neural Information Processing Systems http://nips.cc/
MinimumSteinDiscrepancyEstimators
Examples of such models arise naturally in modelling images [27, 39], natural language [54], Markov random fields [61] and nonparametric density estimation [63, 69].