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20172021
most citedAlgaeDICE: Policy Gradient from Arbitrary Experience

80 citations · 382 across the 19 of their papers we have counts for

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28 papers · 1 filter

cs.LG20217 cited

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

Hongyu Ren, Hanjun Dai, Bo Dai +4

Knowledge graphs (KGs) capture knowledge in the form of head--relation--tail triples and are a crucial component in many AI systems. There are two important reasoning tasks on KGs:…

cs.LG2021

Understanding the Effect of Stochasticity in Policy Optimization

Jincheng Mei, Bo Dai, Chenjun Xiao +2

We study the effect of stochasticity in on-policy policy optimization, and make the following four contributions. First, we show that the preferability of optimization methods depe…

cs.LG202128 cited

Combiner: Full Attention Transformer with Sparse Computation Cost

Hongyu Ren, Hanjun Dai, Zihang Dai +4

Transformers provide a class of expressive architectures that are extremely effective for sequence modeling. However, the key limitation of transformers is their quadratic memory a…

cs.LG20212 cited

Optimization Variance: Exploring Generalization Properties of DNNs

Xiao Zhang, Dongrui Wu, Haoyi Xiong +1

Unlike the conventional wisdom in statistical learning theory, the test error of a deep neural network (DNN) often demonstrates double descent: as the model complexity increases, i…

cs.LG20212 cited

On the Optimality of Batch Policy Optimization Algorithms

Chenjun Xiao, Yifan Wu, Tor Lattimore +5

Batch policy optimization considers leveraging existing data for policy construction before interacting with an environment. Although interest in this problem has grown significant…

cs.LG20217 cited

Off-Policy Imitation Learning from Observations

Zhuangdi Zhu, Kaixiang Lin, Bo Dai +1

Learning from Observations (LfO) is a practical reinforcement learning scenario from which many applications can benefit through the reuse of incomplete resources. Compared to conv…