52 citations · 102 across the 8 of their papers we have counts for
8 papers
MultiBalance: Multi-Objective Gradient Balancing in Industrial-Scale Multi-Task Recommendation System
Yun He, Xuxing Chen, Jiayi Xu +11
In industrial recommendation systems, multi-task learning (learning multiple tasks simultaneously on a single model) is a predominant approach to save training/serving resources an…
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
YiFan Zhang, Weiqi Chen, Zhaoyang Zhu +7
Online updating of time series forecasting models aims to tackle the challenge of concept drifting by adjusting forecasting models based on streaming data. While numerous algorithm…
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
Yanjun Zhao, Tian Zhou, Chao Chen +3
Time series analysis is vital for numerous applications, and transformers have become increasingly prominent in this domain. Leading methods customize the transformer architecture…
Attention as Robust Representation for Time Series Forecasting
PeiSong Niu, Tian Zhou, Xue Wang +2
Time series forecasting is essential for many practical applications, with the adoption of transformer-based models on the rise due to their impressive performance in NLP and CV. T…
Free Lunch for Domain Adversarial Training: Environment Label Smoothing
YiFan Zhang, Xue Wang, Jian Liang +4
A fundamental challenge for machine learning models is how to generalize learned models for out-of-distribution (OOD) data. Among various approaches, exploiting invariant features…
A Novel Convergence Analysis for Algorithms of the Adam Family
Zhishuai Guo, Yi Xu, Wotao Yin +2
Since its invention in 2014, the Adam optimizer has received tremendous attention. On one hand, it has been widely used in deep learning and many variants have been proposed, while…