354 citations · 2.1k across the 86 of their papers we have counts for
8 papers · 1 filter
Hyperparameter Learning via Distributional Transfer
Ho Chung Leon Law, Peilin Zhao, Lucian Chan +2
Bayesian optimisation is a popular technique for hyperparameter learning but typically requires initial exploration even in cases where similar prior tasks have been solved. We pro…
Dual Reconstruction Nets for Image Super-Resolution with Gradient Sensitive Loss
Yong Guo, Qi Chen, Jian Chen +5
Deep neural networks have exhibited promising performance in image super-resolution (SR) due to the power in learning the non-linear mapping from low-resolution (LR) images to high…
Distributed Collaborative Hashing and Its Applications in Ant Financial
Chaochao Chen, Ziqi Liu, Peilin Zhao +3
Collaborative filtering, especially latent factor model, has been popularly used in personalized recommendation. Latent factor model aims to learn user and item latent factors from…
Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication
Zebang Shen, Aryan Mokhtari, Tengfei Zhou +2
Recently, the decentralized optimization problem is attracting growing attention. Most existing methods are deterministic with high per-iteration cost and have a convergence rate q…
A Boosting Framework of Factorization Machine
Longfei Li, Peilin Zhao, Jun Zhou +1
Recently, Factorization Machines (FM) has become more and more popular for recommendation systems, due to its effectiveness in finding informative interactions between features. Us…
Adaptive Cost-sensitive Online Classification
Peilin Zhao, Yifan Zhang, Min Wu +3
Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i…
Online Compact Convexified Factorization Machine
Wenpeng Zhang, Xiao Lin, Peilin Zhao
Factorization Machine (FM) is a supervised learning approach with a powerful capability of feature engineering. It yields state-of-the-art performance in various batch learning tas…
Online Learning: A Comprehensive Survey
Steven C. H. Hoi, Doyen Sahoo, Jing Lu +1
Online learning represents an important family of machine learning algorithms, in which a learner attempts to resolve an online prediction (or any type of decision-making) task by…