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

October 22, 2024

Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning
Dongsu Lee, Minhae Kwon
Reinforcement Learning LeArning Abstract Multi Agent Interaction Multi User Episodic Future Thinking

October 21, 2024

Gradient-Free Supervised Learning using Spike-Timing-Dependent Plasticity for Image Recognition
Wei Xie
Neural Network LeArning Abstract Supervised Learning Back Propagation Image Recognition Plasticity Rule Gradient Free Spike Timing Dependent Plasticity
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning using Packed Secret Sharing
Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou
LeArning Abstract Differential Privacy Privacy Utility Secret Sharing Unfolded D ADMM Cryptographic Protocol Differentially Private Federated Learning
Towards Combating Frequency Simplicity-biased Learning for Domain Generalization
Xilin He, Jingyu Hu, Qinliang Lin, Cheng Luo, Weicheng Xie, Siyang Song, Muhammad Haris Khan, Linlin Shen
LeArning Abstract Strong Generalization Domain Generalization Generalization Performance Internet Service Domain Exercise Repetition
Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning
Ronglong Fang, Yuesheng Xu
LeArning Abstract Deep Neural Network Deep Learning Model Shallow Neural Network Frequency Feature Spectral Bias
Distributed Learning for UAV Swarms
Chen Hu, Hanchi Ren, Jingjing Deng, Xianghua Xie
LeArning Abstract Unmanned Aerial Vehicle Various Fast Moving Drone UAV Swarm
Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning
Wenzhe Fan, Zishun Yu, Chengdong Ma, Changye Li, Yaodong Yang, Xinhua Zhang
LeArning Abstract Multi Agent Reinforcement Learning Positive Reinforcement Graph Model Encoder Decoder Architecture Efficient Collaboration Transformer Agent
Learning to Synthesize Graphics Programs for Geometric Artworks
Qi Bing, Chaoyi Zhang, Weidong Cai
LeArning Abstract Program Synthesis Input Image Geometric Shape Digital Art

October 20, 2024

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning
Heshan Fernando, Han Shen, Parikshit Ram, Yi Zhou, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen
LeArning Abstract Anti Forgetting Preference Feedback Preference Learning LLM Fine Tuning Sequential Learning
Bayesian data fusion for distributed learning
Peng Wu, Tales Imbiriba, Pau Closas
LeArning Abstract Cluster Structure Probabilistic Fusion Data Association Client Clustering
AssemblyComplete: 3D Combinatorial Construction with Deep Reinforcement Learning
Alan Chen, Changliu Liu
LeArning Abstract Robotics Domain Assembly Task Deep Reinforcement 3D Graph
log-RRIM: Yield Prediction via Local-to-global Reaction Representation Learning and Interaction Modeling
Xiao Hu, Ziqi Chen, Bo Peng, Daniel Adu-Ampratwum, Xia Ning
LeArning Abstract Yield Prediction Molecular Information Interaction Modeling Chemical Synthesis Reaction Representation Reaction Yield Prediction
Symmetry Nonnegative Matrix Factorization Algorithm Based on Self-paced Learning
Lei Wang, Liang Du, Peng Zhou, Peng Wu
LeArning Abstract Practical Algorithm Cluster Analysis Self Generated Symmetric Nonnegative Matrix Factorization
TAGExplainer: Narrating Graph Explanations for Text-Attributed Graph Learning Models
Bo Pan, Zhen Xiong, Guanchen Wu, Zheng Zhang, Yifei Zhang, Liang Zhao
LeArning Abstract Graph Drawing Natural Language Explanation Learning Model Graph Explainability
GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric Learning
Haiwen Diao, Ying Zhang, Shang Gao, Jiawen Zhu, Long Chen, Huchuan Lu
LeArning Abstract Structured Sparsity Multimodal Retrieval Pairwise Similarity Fine Grained Image Retrieval Graph Smoothing

October 19, 2024

FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
Sizhe Liu, Jun Xia, Lecheng Zhang, Yuchen Liu, Yue Liu, Wenjie Du, Zhangyang Gao, Bozhen Hu, Cheng Tan, Hongxin Xiang, Stan Z. Li
LeArning Abstract Flexible Toolkit Protein Sequence Encoder
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
Woojin Chae, Kihyuk Hong, Yufan Zhang, Ambuj Tewari, Dabeen Lee
LeArning Abstract Regret Guarantee Norm Bounded Minimax Optimal Regret Linear Mixture Markov Decision Process Substitute Span

LeArning Abstract

Papers

Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning

Gradient-Free Supervised Learning using Spike-Timing-Dependent Plasticity for Image Recognition

DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning using Packed Secret Sharing

Towards Combating Frequency Simplicity-biased Learning for Domain Generalization

Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning

Distributed Learning for UAV Swarms

Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning

Learning to Synthesize Graphics Programs for Geometric Artworks

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning

Bayesian data fusion for distributed learning

AssemblyComplete: 3D Combinatorial Construction with Deep Reinforcement Learning

log-RRIM: Yield Prediction via Local-to-global Reaction Representation Learning and Interaction Modeling

Symmetry Nonnegative Matrix Factorization Algorithm Based on Self-paced Learning

TAGExplainer: Narrating Graph Explanations for Text-Attributed Graph Learning Models

GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric Learning

FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning

Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span

Learning With Multi-Group Guarantees For Clusterable Subpopulations

Using Sentiment and Technical Analysis to Predict Bitcoin with Machine Learning

SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery