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PolicyPolicyUpdates
We tackle this planning issue by extending the policy gradient theory to policy updates with respecttoanystatedensity.
Boosting Learning for LDPC Codes to Improve the Error-Floor Performance
These works assume an arbitrary neural network with no prior knowledge of decoding algorithms, and accordingly, face the challenge of learning a decoding algorithm.
Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning
Social media platforms capture diverse attack sequence samples through both machine and manual screening processes. Investigating effective ways to leverage these adversarial samples to enhance robustness is imperative.
OnAnalyzingGenerativeandDenoisingCapabilities ofDiffusion-basedDeepGenerativeModels
While the performance of DDGMs is impressive, not all of their aspects are fully understood.
On the Power of Edge Independent Graph Models
Why do many modern neural-network-based graph generative models fail to reproduce typical real-world network characteristics, such as high triangle density?