2 citations · 2 across the 5 of their papers we have counts for
5 papers
LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation
Shali Jiang, Hua Zheng, Boyang Liu +46
Knowledge distillation (KD) transfers a single scalar prediction from a large foundation model (FM) to compact vertical models (VMs), suffering from diminishing transfer ratio -- t…
Expressive Power of Implicit Models: Rich Equilibria and Test-Time Scaling
Jialin Liu, Lisang Ding, Stanley Osher +1
Implicit models, an emerging model class, compute outputs by iterating a single parameter block to a fixed point. This architecture realizes an infinite-depth, weight-tied network…
Efficient Algorithms for Sum-of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang +1
In this work, we propose a novel optimization model termed "sum-of-minimum" optimization. This model seeks to minimize the sum or average of objective functions over parame…
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
Lisang Ding, Kexin Jin, Bicheng Ying +2
Decentralized Stochastic Gradient Descent (SGD) is an emerging neural network training approach that enables multiple agents to train a model collaboratively and simultaneously. Ra…
A mean field game inverse problem
Lisang Ding, Wuchen Li, Stanley Osher +1
Mean-field games arise in various fields including economics, engineering, and machine learning. They study strategic decision making in large populations where the individuals int…