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Ji Liu

59 papers hereh-index 5314.8k citations180 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author24
  • last author28

Across the 53 of 59 papers where every author was matched, so the position is known.

fields
  • cs.LG27
  • cs.CV8
  • cs.DC5
  • cs.AI4
  • math.OC4
  • stat.ML4
same name
  • Ji Liu — 17 papers, h 30
  • Ji Liu — 9 papers
  • Ji Liu — 7 papers
  • Ji Liu — 6 papers
  • Ji Liu — 6 papers
  • Ji Liu — 5 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172021
most citedGlobal Sparse Momentum SGD for Pruning Very Deep Neural Networks

125 citations · 409 across the 32 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2020

Stochastic Recursive Momentum for Policy Gradient Methods

Huizhuo Yuan, Xiangru Lian, Ji Liu +1

In this paper, we propose a novel algorithm named STOchastic Recursive Momentum for Policy Gradient (STORM-PG), which operates a SARAH-type stochastic recursive variance-reduced po…

stat.ML2020★ 4 cited

Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization

Huizhuo Yuan, Xiangru Lian, Ji Liu

Stochastic compositional optimization arises in many important machine learning tasks such as value function evaluation in reinforcement learning and portfolio management. The obje…

stat.ML2017★ 12 cited

Variance Reduced methods for Non-convex Composition Optimization

Liu Liu, Ji Liu, Dacheng Tao

This paper explores the non-convex composition optimization in the form including inner and outer finite-sum functions with a large number of component functions. This problem aris…

stat.ML2017

Duality-free Methods for Stochastic Composition Optimization

Liu Liu, Ji Liu, Dacheng Tao

We consider the composition optimization with two expected-value functions in the form of n1​∑i=1n​Fi​(m1​∑j=1m​Gj​(x))+R(x),…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.