LeArning Abstract

Learning, in the context of these papers, encompasses a broad range of research focused on improving the efficiency, robustness, and adaptability of machine learning models across diverse applications. Current efforts concentrate on developing novel self-supervised learning techniques, particularly for structured data like tabular formats, and on leveraging low-rank adaptations for efficient fine-tuning of large language and other foundation models. These advancements are significant because they address key challenges in data efficiency, computational cost, and the generalization capabilities of machine learning systems, impacting fields ranging from personalized medicine to autonomous robotics.

Papers

December 13, 2024

Controlling dynamical systems into unseen target states using machine learning
Daniel Köglmayr, Alexander Haluszczynski, Christoph Räth
LeArning Abstract New Machine Dynamical System Reservoir Computing Complex Dynamical System Complex Dynamic Unseen Target
Label-template based Few-Shot Text Classification with Contrastive Learning
Guanghua Hou, Shuhui Cao, Deqiang Ouyang, Ning Wang
LeArning Abstract Label Information Contrastive Example Semantic Label Shot Text Classification
Sharpening Your Density Fields: Spiking Neuron Aided Fast Geometry Learning
Yi Gu, Zhaorui Wang, Dongjun Ye, Renjing Xu
LeArning Abstract Neural Radiance Field Neural Topic Geometric Learning Threshold Based Density Field Neural Geometry
Temporal Causal Discovery in Dynamic Bayesian Networks Using Federated Learning
Jianhong Chen, Ying Ma, Xubo Yue
LeArning Abstract Optimization Purpose Federated Prompt Cooperation Structure Learning Continuous Optimization Dynamic Bayesian Network Temporal Causal Discovery
Learning Visually Grounded Domain Ontologies via Embodied Conversation and Explanation
Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy
LeArning Abstract Line by Line Explanation Top Level Ontology Domain Ontology Hypothesis Space B Learner
A Novel Methodology in Credit Spread Prediction Based on Ensemble Learning and Feature Selection
Yu Shao, Jiawen Bai, Yingze Hou, Xia'an Zhou, Zhanhao Pan
LeArning Abstract Feature Selection Diverse Ensemble New Method Risk Prediction Default Prediction

December 12, 2024

Congruence-based Learning of Probabilistic Deterministic Finite Automata
Matías Carrasco, Franz Mayr, Sergio Yovine
Language Model LeArning Abstract Active Learning Algorithm Product Automaton Formal Language Probabilistic Deterministic Finite Automaton
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao, Le Gan, De-Chuan Zhan, Han-Jia Ye
LeArning Abstract Pre Trained Catastrophic Forgetting Class Incremental Learning Anti Forgetting Parameter Efficient Adapter
SVasP: Self-Versatility Adversarial Style Perturbation for Cross-Domain Few-Shot Learning
Wenqian Li, Pengfei Fang, Hui Xue
LeArning Abstract Adversarial Perturbation Gradient Clipping Adversarial Feature
Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning
Wenna Lai, Haoran Xie, Guandong Xu, Qing Li
Large Language Model LeArning Abstract Raw Data Multi Task Learning Implicit Sentiment User Sentiment Weight Freezing Task Specific Weight
Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification
Haocong Rao, Chunyan Miao
LeArning Abstract Graph Neural Network Skeleton Representation Skeleton Data Skeleton Graph Prototype Contrastive Learning
Learning and Current Prediction of PMSM Drive via Differential Neural Networks
Wenjie Mei, Xiaorui Wang, Yanrong Lu, Ke Yu, Shihua Li
LeArning Abstract Network Programming Dynamical System Nonlinear Dynamic Synchronous Generator State Prediction
Stellar parameter prediction and spectral simulation using machine learning
Vojtěch Cvrček, Martino Romaniello, Radim Šára, Wolfram Freudling, Pascal Ballester
LeArning Abstract New Machine Reference Dataset Spectral Model Stellar Parameter Radial Velocity Stellar Spectrum
Structurally Consistent MRI Colorization using Cross-modal Fusion Learning
Mayuri Mathur, Anav Chaudhary, Saurabh Kumar Gupta, Ojaswa Sharma
LeArning Abstract Image Colorization Color Transfer
Words of War: Exploring the Presidential Rhetorical Arsenal with Deep Learning
Wyatt Scott, Brett Genz, Sarah Elmasry, Sodiq Adewole
LeArning Abstract Word List Political Discourse Rhetorical Structure

December 11, 2024

Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning
Prajwal Koirala, Zhanhong Jiang, Soumik Sarkar, Cody Fleming
LeArning Abstract Intermediate Latent Conditional Variational Offline Safe Reinforcement Learning
TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
Jimmy Wu, William Chong, Robert Holmberg, Aaditya Prasad, Yihuai Gao, Oussama Khatib, Shuran Song, Szymon Rusinkiewicz, Jeannette Bohg
LeArning Abstract Robot Person Imitation Learning Mobile Manipulator Mobile Manipulation Teleoperation Framework
Learning Sketch Decompositions in Planning via Deep Reinforcement Learning
Michael Aichmüller, Hector Geffner
Reinforcement Learning LeArning Abstract Deep Reinforcement Learning Task Planning Deep Reinforcement Classical Planning Sketch Based Sketch Extraction
Improving Satellite Imagery Masking using Multi-task and Transfer Learning
Rangel Daroya, Luisa Vieira Lucchese, Travis Simmons, Punwath Prum, Tamlin Pavelsky, John Gardner, Colin J. Gleason, Subhransu Maji
LeArning Abstract Multi Task Formality Transfer Satellite Imagery Mask Guided Cloud Detection Landsat 8
Protecting Confidentiality, Privacy and Integrity in Collaborative Learning
Dong Chen, Alice Dethise, Istemi Ekin Akkus, Ivica Rimac, Klaus Satzke, Antti Koskela, Marco Canini, Wei Wang, Ruichuan Chen
LeArning Abstract Differential Privacy Privacy Policy Model Training Privacy Mechanism Privacy Preserving Training Dataset Management

LeArning Abstract

Papers

Controlling dynamical systems into unseen target states using machine learning

Label-template based Few-Shot Text Classification with Contrastive Learning

Sharpening Your Density Fields: Spiking Neuron Aided Fast Geometry Learning

Temporal Causal Discovery in Dynamic Bayesian Networks Using Federated Learning

Learning Visually Grounded Domain Ontologies via Embodied Conversation and Explanation

A Novel Methodology in Credit Spread Prediction Based on Ensemble Learning and Feature Selection

Congruence-based Learning of Probabilistic Deterministic Finite Automata

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning

SVasP: Self-Versatility Adversarial Style Perturbation for Cross-Domain Few-Shot Learning

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning

Motif Guided Graph Transformer with Combinatorial Skeleton Prototype Learning for Skeleton-Based Person Re-Identification

Learning and Current Prediction of PMSM Drive via Differential Neural Networks

Stellar parameter prediction and spectral simulation using machine learning

Structurally Consistent MRI Colorization using Cross-modal Fusion Learning

Words of War: Exploring the Presidential Rhetorical Arsenal with Deep Learning

Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning

TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning

Learning Sketch Decompositions in Planning via Deep Reinforcement Learning

Improving Satellite Imagery Masking using Multi-task and Transfer Learning

Protecting Confidentiality, Privacy and Integrity in Collaborative Learning