104 citations · 498 across the 23 of their papers we have counts for
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Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation
Junwei Huang, Zhiqing Sun, Yiming Yang
Graph-based diffusion models have shown promising results in terms of generating high-quality solutions to NP-complete (NPC) combinatorial optimization (CO) problems. However, thos…
Balancing Exploration and Exploitation in Hierarchical Reinforcement Learning via Latent Landmark Graphs
Qingyang Zhang, Yiming Yang, Jingqing Ruan +3
Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) is a promising paradigm to address the exploration-exploitation dilemma in reinforcement learning. It decomposes the so…
CH-Go: Online Go System Based on Chunk Data Storage
H. Lu, C. Li, Y. Yang +1
The training and running of an online Go system require the support of effective data management systems to deal with vast data, such as the initial Go game records, the feature da…
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization
Zhiqing Sun, Yiming Yang
Neural network-based Combinatorial Optimization (CO) methods have shown promising results in solving various NP-complete (NPC) problems without relying on hand-crafted domain knowl…
Traffic4cast at NeurIPS 2021 -- Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
Christian Eichenberger, Moritz Neun, Henry Martin +34
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggrega…
An EM Approach to Non-autoregressive Conditional Sequence Generation
Zhiqing Sun, Yiming Yang
Autoregressive (AR) models have been the dominating approach to conditional sequence generation, but are suffering from the issue of high inference latency. Non-autoregressive (NAR…