80 citations · 168 across the 8 of their papers we have counts for
7 papers · 1 filter
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series
Qingsong Wen, Jingkun Gao, Xiaomin Song +3
Decomposing complex time series into trend, seasonality, and remainder components is an important task to facilitate time series anomaly detection and forecasting. Although numerou…
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
Hao Yu, Sen Yang, Shenghuo Zhu
In distributed training of deep neural networks, parallel mini-batch SGD is widely used to speed up the training process by using multiple workers. It uses multiple workers to samp…
Large-scale Distance Metric Learning with Uncertainty
Qi Qian, Jiasheng Tang, Hao Li +2
Distance metric learning (DML) has been studied extensively in the past decades for its superior performance with distance-based algorithms. Most of the existing methods propose to…
Learning with Non-Convex Truncated Losses by SGD
Yi Xu, Shenghuo Zhu, Sen Yang +3
Learning with a {\it convex loss} function has been a dominating paradigm for many years. It remains an interesting question how non-convex loss functions help improve the generali…
Robust Optimization over Multiple Domains
Qi Qian, Shenghuo Zhu, Jiasheng Tang +3
In this work, we study the problem of learning a single model for multiple domains. Unlike the conventional machine learning scenario where each domain can have the corresponding m…
Multinomial Logit Bandit with Linear Utility Functions
Mingdong Ou, Nan Li, Shenghuo Zhu +1
Multinomial logit bandit is a sequential subset selection problem which arises in many applications. In each round, the player selects a -cardinality subset from candidate i…