Supervised Learning

Supervised learning, a core machine learning paradigm, aims to train models to predict outputs based on labeled input data. Current research emphasizes improving model efficiency and robustness, particularly in scenarios with limited or noisy data, exploring techniques like self-supervised pre-training, active learning for data selection, and ensemble methods to enhance accuracy and address class imbalances. These advancements are crucial for various applications, from medical image analysis and infrastructure inspection to natural language processing and targeted advertising, enabling more accurate and reliable predictions with less reliance on extensive labeled datasets.

Papers

November 22, 2023

Learning principle and mathematical realization of the learning mechanism in the brain
Taisuke Katayose
Deep Learning LeArning Abstract Supervised Learning Unsupervised Learning Brain Function General Principle Learning Mechanism Mathematical Discovery

November 16, 2023

Comparing Differentiable Logics for Learning Systems: A Research Preview
Thomas Flinkow, Barak A. Pearlmutter, Rosemary Monahan
Machine Learning Machine Learning Model Supervised Learning DH Research Background Knowledge Learning System Differentiable Logic

November 15, 2023

November 2, 2023

An Integrated Framework Integrating Monte Carlo Tree Search and Supervised Learning for Train Timetabling Problem
Feiyu Yang
Supervised Learning Monte Carlo Tree Search Right Problem Specific Heuristic High Speed Train System

October 30, 2023

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du
Supervised Learning Policy Learning Policy Reinforcement Learning Model Based Dynamic Programming Q$ Learning Based Offline RL Trajectory Stitching Bellman Completeness

October 28, 2023

SSL Framework for Causal Inconsistency between Structures and Representations
Hang Chen, Xinyu Yang, Keqing Du, Wenya Wang
Supervised Learning Causal Discovery Meaningful Representation Causal Structure Causal Relationship Simple Structure

October 25, 2023

Graph-based multimodal multi-lesion DLBCL treatment response prediction from PET images
Oriane Thiery, Mira Rizkallah, Clément Bailly, Caroline Bodet-Milin, Emmanuel Itti, René-Olivier Casasnovas, Steven Le Gouill, Thomas Carlier, Diana Mateus
Supervised Learning Positron Emission Tomography Imaging Data Large B Cell Lymphoma Free Survival

October 23, 2023

Bayesian Regression Markets
Thomas Falconer, Jalal Kazempour, Pierre Pinson
Supervised Learning Regression Task Machine Learning Task Regression Market

October 22, 2023

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation
Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang
Generative Model Generative Adversarial Network Supervised Learning Density Estimation Score Based Diffusion Model

October 16, 2023

Advantages of Machine Learning in Bus Transport Analysis
Amirsadegh Roshanzamir
Machine Learning Supervised Learning Supervised Machine Learning Public Transit Advantage Feedback Route Recommendation

October 15, 2023

CAPro: Webly Supervised Learning with Cross-Modality Aligned Prototypes
Yulei Qin, Xingyu Chen, Yunhang Shen, Chaoyou Fu, Yun Gu, Ke Li, Xing Sun, Rongrong Ji
Supervised Learning Visual Representation Cross Modality Visual Prototype Fine Grained Visual Prototypical Contrastive Learning Latent Prototype

September 28, 2023

Supervised Learning Models for Early Detection of Albuminuria Risk in Type-2 Diabetes Mellitus Patients
Arief Purnama Muharram, Dicky Levenus Tahapary, Yeni Dwi Lestari, Randy Sarayar, Valerie Josephine Dirjayanto
Supervised Learning Early Detection Type 2 Diabetes Chronic Kidney Disease

September 26, 2023

On Excess Risk Convergence Rates of Neural Network Classifiers
Hyunouk Ko, Namjoon Suh, Xiaoming Huo
Neural Network Supervised Learning Convergence Rate Classification Problem Neural Network Classifier

September 22, 2023

Unsupervised Representations Improve Supervised Learning in Speech Emotion Recognition
Amirali Soltani Tehrani, Niloufar Faridani, Ramin Toosi
Emotion Recognition Supervised Learning Speech Emotion Recognition Unsupervised Representation

September 15, 2023

SSL-Net: A Synergistic Spectral and Learning-based Network for Efficient Bird Sound Classification
Yiyuan Yang, Kaichen Zhou, Niki Trigoni, Andrew Markham
Supervised Learning Audio Datasets Synergistic Information Animal Sound Bird Sound Network Learning

September 12, 2023

Using Unsupervised and Supervised Learning and Digital Twin for Deep Convective Ice Storm Classification
Jason Swope, Steve Chien, Emily Dunkel, Xavier Bosch-Lluis, Qing Yue, William Deal
Supervised Learning Digital Twin Unsupervised Setting Radiomics Feature Non Storm Cloud Cloud Classification

September 10, 2023

Is Learning in Biological Neural Networks based on Stochastic Gradient Descent? An analysis using stochastic processes
Sören Christensen, Jan Kallsen
Neural Network General Analysis Stochastic Gradient Descent Supervised Learning Stochastic Process Biological Neural Network Stochastic Gradient Based

September 7, 2023

Supervised Learning and Large Language Model Benchmarks on Mental Health Datasets: Cognitive Distortions and Suicidal Risks in Chinese Social Media
Hongzhi Qi, Qing Zhao, Jianqiang Li, Changwei Song, Wei Zhai, Dan Luo, Shuo Liu, Yi Jing Yu, Fan Wang, Huijing Zou, Bing Xiang Yang, Guanghui Fu
Large Language Model Supervised Learning Mental Health Suicide Risk Weibo Dataset Cognitive Distortion

September 5, 2023

A Survey of the Impact of Self-Supervised Pretraining for Diagnostic Tasks with Radiological Images
Blake VanBerlo, Jesse Hoey, Alexander Wong
Timely Survey Self Supervised Learning Transfer Learning Global Impact Supervised Learning Self Supervised Pretraining Self Supervised Learning Method Radiology Image Diagnosis Task

Supervised Learning

Papers

Learning principle and mathematical realization of the learning mechanism in the brain

Comparing Differentiable Logics for Learning Systems: A Research Preview

Few-shot Transfer Learning for Knowledge Base Question Answering: Fusing Supervised Models with In-Context Learning

Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty

An Integrated Framework Integrating Monte Carlo Tree Search and Supervised Learning for Train Timetabling Problem

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning

SSL Framework for Causal Inconsistency between Structures and Representations

Graph-based multimodal multi-lesion DLBCL treatment response prediction from PET images

Bayesian Regression Markets

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation

Advantages of Machine Learning in Bus Transport Analysis

CAPro: Webly Supervised Learning with Cross-Modality Aligned Prototypes

Supervised Learning Models for Early Detection of Albuminuria Risk in Type-2 Diabetes Mellitus Patients

On Excess Risk Convergence Rates of Neural Network Classifiers

Unsupervised Representations Improve Supervised Learning in Speech Emotion Recognition

SSL-Net: A Synergistic Spectral and Learning-based Network for Efficient Bird Sound Classification

Using Unsupervised and Supervised Learning and Digital Twin for Deep Convective Ice Storm Classification

Is Learning in Biological Neural Networks based on Stochastic Gradient Descent? An analysis using stochastic processes

Supervised Learning and Large Language Model Benchmarks on Mental Health Datasets: Cognitive Distortions and Suicidal Risks in Chinese Social Media

A Survey of the Impact of Self-Supervised Pretraining for Diagnostic Tasks with Radiological Images