research
∙
09/03/2023
Multidomain transformer-based deep learning for early detection of network intrusion
Timely response of Network Intrusion Detection Systems (NIDS) is constra...
share
research
∙
07/19/2023
STRAPPER: Preference-based Reinforcement Learning via Self-training Augmentation and Peer Regularization
Preference-based reinforcement learning (PbRL) promises to learn a compl...
research
∙
06/26/2023
CEIL: Generalized Contextual Imitation Learning
In this paper, we present ContExtual Imitation Learning (CEIL), a genera...
research
∙
06/23/2023
CLUE: Calibrated Latent Guidance for Offline Reinforcement Learning
Offline reinforcement learning (RL) aims to learn an optimal policy from...
research
∙
06/15/2023
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
The unprecedented performance of large language models (LLMs) necessitat...
research
∙
05/25/2023
Beyond Reward: Offline Preference-guided Policy Optimization
This study focuses on the topic of offline preference-based reinforcemen...
research
∙
05/23/2023
Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
The robustness to distribution changes ensures that NLP models can be su...
research
∙
02/22/2023
Behavior Proximal Policy Optimization
Offline reinforcement learning (RL) is a challenging setting where exist...
research
∙
10/08/2022
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction
Document-level relation extraction with graph neural networks faces a fu...
research
∙
08/10/2022
Collaborative Feature Maps of Networks and Hosts for AI-driven Intrusion Detection
Intrusion Detection Systems (IDS) are critical security mechanisms that ...
research
∙
04/07/2022
Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats
Despite its technological benefits, Internet of Things (IoT) has cyber w...
research
∙
03/13/2022
DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning
Offline reinforcement learning algorithms promise to be applicable in se...
research
∙
10/25/2021
Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning
Unsupervised reinforcement learning aims to acquire skills without prior...
research
∙
10/21/2021
Off-Dynamics Inverse Reinforcement Learning from Hetero-Domain
We propose an approach for inverse reinforcement learning from hetero-do...
research
∙
08/29/2021
Risk-Aware Fine-Grained Access Control in Cyber-Physical Contexts
Access to resources by users may need to be granted only upon certain co...
research
∙
04/11/2021
Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning
It is of significance for an agent to learn a widely applicable and gene...
research
∙
06/03/2020
