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Found 5 papers, 2 papers with code
Improving the Performance of R17 Type-II Codebook with Deep Learning
The Type-II codebook in Release 17 (R17) exploits the angular-delay-domain partial reciprocity between uplink and downlink channels to select part of angular-delay-domain ports for measuring and feeding back the downlink channel state information (CSI), where the performance of existing deep learning enhanced CSI feedback methods is limited due to the deficiency of sparse structures.
Deep Learning Empowered Type-II Codebook: New Paradigm for Enhancing CSI Feedback
In contrast to its counterpart in Release 16, the Type-II codebook in Release 17 (R17) exploits the angular-delay-domain partial reciprocity between uplink and downlink channels and selects part of angular-delay-domain ports for measuring and feeding back the downlink CSI, where the performance of the conventional deep learning methods is limited due to the deficiency of sparse structures.
Anti-Overestimation Dialogue Policy Learning for Task-Completion Dialogue System
This problem is detrimental to RL-based dialogue policy learning.
Paint4Poem: A Dataset for Artistic Visualization of Classical Chinese Poems
We create abenchmark for Paint4Poem: we train two representative text-to-image generation models: AttnGAN and MirrorGAN, and evaluate theirperformance regarding painting pictorial quality, painting stylistic relevance, and semantic relevance between poems and paintings. The results indicate that the models are able to generate paintings that have good pictorial quality and mimic Feng Zikai's style, but thereflection of poem semantics is limited.
Successive Convex Approximation Based Off-Policy Optimization for Constrained Reinforcement Learning
We propose a successive convex approximation based off-policy optimization (SCAOPO) algorithm to solve the general constrained reinforcement learning problem, which is formulated as a constrained Markov decision process (CMDP) in the context of average cost.
