3 citations · 3 across the 17 of their papers we have counts for
6 papers · 1 filter
Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting
Jinjin Chi, Lei Feng, Lulu Zhang +6
Time series foundation models (TSFMs) have recently achieved strong zero-shot forecasting performance through large-scale pretraining and retrieval-augmented prediction. However, o…
Generalizing Dynamics Modeling More Easily from Representation Perspective
Yiming Wang, Zhengnan Zhang, Genghe Zhang +7
Learning system dynamics from observations is a critical problem in many applications over various real-world complex systems, e.g., climate, ecology, and fluid systems. Recently,…
Learning from Label Proportions with Dual-proportion Constraints
Tianhao Ma, Ximing Li, Changchun Li +1
Learning from Label Proportions (LLP) is a weakly supervised problem in which the training data comprise bags, that is, groups of instances, each annotated only with bag-level clas…
Semi-Supervised Learning with Balanced Deep Representation Distributions
Changchun Li, Ximing Li, Bingjie Zhang +2
Semi-Supervised Text Classification (SSTC) mainly works under the spirit of self-training. They initialize the deep classifier by training over labeled texts; and then alternativel…
Harmful Visual Content Manipulation Matters in Misinformation Detection Under Multimedia Scenarios
Bing Wang, Ximing Li, Changchun Li +4
Nowadays, the widespread dissemination of misinformation across numerous social media platforms has led to severe negative effects on society. To address this challenge, the automa…
Recovering Accurate Labeling Information from Partially Valid Data for Effective Multi-Label Learning
Ximing Li, Yang Wang
Partial Multi-label Learning (PML) aims to induce the multi-label predictor from datasets with noisy supervision, where each training instance is associated with several candidate…