Research map / Learning theory and algorithms / Kernels and regression theory
Weakly Supervised Regression with Interval Targets
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Train by penalizing predictions outside the annotated interval with the limiting method | RIT regression models · AgeDB, q=30 | MSE: 116.14 -> 115.76 | Helped |
| Train by penalizing predictions outside the annotated interval with the limiting method | RIT regression models · IMDB-WIKI, q=40 | MSE: 135.57 -> 133.98 | Helped |
| Train by penalizing predictions outside the annotated interval with the limiting method | MLP regression models · Abalone, q=30 | MSE: 5.45 -> 4.66 | Helped |
| Use the middlemost interval value rather than the leftmost value as the training target | Selection-based RIT regression · AgeDB, q=30 | MSE: 134.99 -> 116.14 | Helped |
| Use the middlemost interval value rather than the rightmost value as the training target | Selection-based RIT regression · AgeDB, q=30 | MSE: 154.87 -> 116.14 | Helped |
| Use the middlemost interval value rather than an endpoint as the target | Selection-based RIT regression · AgeDB interval, interval size a | Expected absolute error: a/2 -> a/4 | Helped |
| Increase the maximum interval size q | RIT methods · AgeDB | MSE: 115.76 -> 129.47 | Hurt |
Closest papers by meaning
- Learning from Interval Targets (NeurIPS 2025 · similarity 0.88)
- Piecewise Constant and Linear Regression Trees: An Optimal Dynamic Programming Approach (ICML 2024 · similarity 0.84)
- CGMatch: A Different Perspective of Semi-supervised Learning (CVPR 2025 · similarity 0.83)
- ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift (ICLR 2024 · similarity 0.83)
- Weak Supervision Performance Evaluation via Partial Identification (NeurIPS 2024 · similarity 0.83)
- Boosting Methods for Interval-censored Data with Regression and Classification (ICLR 2025 · similarity 0.83)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.