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Found 8 papers, 0 papers with code
X-MEN: Guaranteed XOR-Maximum Entropy Constrained Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is a powerful way of learning from demonstrations.
Provable Constrained Stochastic Convex Optimization with XOR-Projected Gradient Descent
Here we propose XOR-PGD, a novel algorithm based on Projected Gradient Descent (PGD) coupled with the XOR sampler, which is guaranteed to solve the constrained stochastic convex optimization problem still in linear convergence rate by choosing proper step size.
A Light-Weighted Convolutional Neural Network for Bitemporal SAR Image Change Detection
We verify our light-weighted neural network on four sets of bitemporal SAR images.
A Convolutional Neural Network with Parallel Multi-Scale Spatial Pooling to Detect Temporal Changes in SAR Images
Furthermore, to verify the generalization of the proposed method, we apply our proposed method to the cross-dataset bitemporal SAR image change detection, where the MSSP network (MSSP-Net) is trained on a dataset and then applied to an unknown testing dataset.
Stein Variational Inference for Discrete Distributions
In addition, such transform can be straightforwardly employed in gradient-free kernelized Stein discrepancy to perform goodness-of-fit (GOF) test on discrete distributions.
Platoon trajectories generation: A unidirectional interconnected LSTM-based car following model
However, the traffic micro-simulation accuracy of car following models in a platoon level, especially during traffic oscillations, still needs to be enhanced.
How to Eliminate Detour Behaviors in E-hailing? Real-time Detecting and Time-dependent Pricing
With the rapid development of information and communication technology (ICT), taxi business becomes a typical electronic commerce mode.
Towards Efficient Discrete Integration via Adaptive Quantile Queries
On a suite of UAI inference challenge benchmarks, it saves 81. 5% of WISH queries while retaining the quality of results.
