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Found 12 papers, 4 papers with code
MRPB 1.0: A Unified Benchmark for the Evaluation of Mobile Robot Local Planning Approaches
Local planning is one of the key technologies for mobile robots to achieve full autonomy and has been widely investigated.
Robotics
FreeEagle: Detecting Complex Neural Trojans in Data-Free Cases
Thus, in this paper, we propose FreeEagle, the first data-free backdoor detection method that can effectively detect complex backdoor attacks on deep neural networks, without relying on the access to any clean samples or samples with the trigger.
Multi-label Classification with High-rank and High-order Label Correlations
Previous methods capture the high-order label correlations mainly by transforming the label matrix to a latent label space with low-rank matrix factorization.
Federated Submodel Optimization for Hot and Cold Data Features
We theoretically proved the convergence rate of FedSubAvg by deriving an upper bound under a new metric called the element-wise gradient norm.
VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control
Recent breakthroughs in Go play and strategic games have witnessed the great potential of reinforcement learning in intelligently scheduling in uncertain environment, but some bottlenecks are also encountered when we generalize this paradigm to universal complex tasks.
Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction
Urban ride-hailing demand prediction is a crucial but challenging task for intelligent transportation system construction.
HpGAN: Sequence Search with Generative Adversarial Networks
Sequences play an important role in many engineering applications and systems.
Dynamic Binary Neural Network by learning channel-wise thresholds
The experimental results prove that our method is an effective and straightforward way to reduce information loss and enhance performance of BNNs.
PTR-PPO: Proximal Policy Optimization with Prioritized Trajectory Replay
In addition, by analyzing the heatmap of priority changes at various locations in the priority memory during training, we find that memory size and rollout length can have a significant impact on the distribution of trajectory priorities and, hence, on the performance of the algorithm.
Boosting Binary Neural Networks via Dynamic Thresholds Learning
For ViTs, DyBinaryCCT presents the superiority of the convolutional embedding layer in fully binarized ViTs and achieves 56. 1% on the ImageNet dataset, which is nearly 9% higher than the baseline.
TextDefense: Adversarial Text Detection based on Word Importance Entropy
TextDefense differs from previous approaches, where it utilizes the target model for detection and thus is attack type agnostic.
Large-scale Generative Simulation Artificial Intelligence: the Next Hotspot in Generative AI
The concept of GenAI has been developed for decades.
