131 citations · 170 across the 7 of their papers we have counts for
7 papers
Fine-grained Private Knowledge Distillation
Yuntong Li, Shaowei Wang, Yingying Wang +4
Knowledge distillation has emerged as a scalable and effective way for privacy-preserving machine learning. One remaining drawback is that it consumes privacy in a model-level (i.e…
Sequential Recommendation in Online Games with Multiple Sequences, Tasks and User Levels
Si Chen, Yuqiu Qian, Hui Li +1
Online gaming is growing faster than ever before, with increasing challenges of providing better user experience. Recommender systems (RS) for online games face unique challenges s…
Fast and Secure Distributed Nonnegative Matrix Factorization
Yuqiu Qian, Conghui Tan, Danhao Ding +2
Nonnegative matrix factorization (NMF) has been successfully applied in several data mining tasks. Recently, there is an increasing interest in the acceleration of NMF, due to its…
Accelerated Dual-Averaging Primal-Dual Method for Composite Convex Minimization
Conghui Tan, Yuqiu Qian, Shiqian Ma +1
Dual averaging-type methods are widely used in industrial machine learning applications due to their ability to promoting solution structure (e.g., sparsity) efficiently. In this p…
An End-to-End Deep RL Framework for Task Arrangement in Crowdsourcing Platforms
Caihua Shan, Nikos Mamoulis, Reynold Cheng +3
In this paper, we propose a Deep Reinforcement Learning (RL) framework for task arrangement, which is a critical problem for the success of crowdsourcing platforms. Previous works…
Beyond Greedy Ranking: Slate Optimization via List-CVAE
Ray Jiang, Sven Gowal, Timothy A. Mann +1
The conventional solution to the recommendation problem greedily ranks individual document candidates by prediction scores. However, this method fails to optimize the slate as a wh…
Barzilai-Borwein Step Size for Stochastic Gradient Descent
Conghui Tan, Shiqian Ma, Yu-Hong Dai +1
One of the major issues in stochastic gradient descent (SGD) methods is how to choose an appropriate step size while running the algorithm. Since the traditional line search techni…