activity
20202025
most citedSDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 2022

58 citations · 160 across the 27 of their papers we have counts for

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10 papers · 1 filter

cs.LG2024★ 1 cited

Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models

Ji Liu, Jiaxiang Ren, Ruoming Jin +4

As a promising paradigm to collaboratively train models with decentralized data, Federated Learning (FL) can be exploited to fine-tune Large Language Models (LLMs). While LLMs corr…

cs.LG2024

A Systematic Review on Long-Tailed Learning

Chongsheng Zhang, George Almpanidis, Gaojuan Fan +6

Long-tailed data is a special type of multi-class imbalanced data with a very large amount of minority/tail classes that have a very significant combined influence. Long-tailed lea…

cs.LG2023★ 3 cited

Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization

Tianshi Che, Ji Liu, Yang Zhou +5

Federated learning (FL) is a promising paradigm to enable collaborative model training with decentralized data. However, the training process of Large Language Models (LLMs) genera…

cs.LG2023★ 1 cited

Multi-Temporal Relationship Inference in Urban Areas

Shuangli Li, Jingbo Zhou, Ji Liu +3

Finding multiple temporal relationships among locations can benefit a bunch of urban applications, such as dynamic offline advertising and smart public transport planning. While so…

cs.LG2022★ 58 cited

SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 2022

Jingbo Zhou, Xinjiang Lu, Yixiong Xiao +4

The variability of wind power supply can present substantial challenges to incorporating wind power into a grid system. Thus, Wind Power Forecasting (WPF) has been widely recognize…

cs.LG2022★ 14 cited

Accelerated Federated Learning with Decoupled Adaptive Optimization

Jiayin Jin, Jiaxiang Ren, Yang Zhou +3

The federated learning (FL) framework enables edge clients to collaboratively learn a shared inference model while keeping privacy of training data on clients. Recently, many heuri…

cs.LG2021

AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow

Haiyan Jiang, Haoyi Xiong, Dongrui Wu +2

Principal component analysis (PCA) has been widely used as an effective technique for feature extraction and dimension reduction. In the High Dimension Low Sample Size (HDLSS) sett…

cs.LG2021★ 24 cited

MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal

Weijia Zhang, Hao Liu, Lijun Zha +4

Real estate appraisal refers to the process of developing an unbiased opinion for real property's market value, which plays a vital role in decision-making for various players in t…

cs.LG2021★ 29 cited

Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond

Xuhong Li, Haoyi Xiong, Xingjian Li +5

Deep neural networks have been well-known for their superb handling of various machine learning and artificial intelligence tasks. However, due to their over-parameterized black-bo…

cs.LG2020★ 1 cited

C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak

Congxi Xiao, Jingbo Zhou, Jizhou Huang +4

The novel coronavirus disease (COVID-19) has crushed daily routines and is still rampaging through the world. Existing solution for nonpharmaceutical interventions usually needs to…