Learning Algorithm

Learning algorithms are computational methods designed to automatically improve performance on a task through experience, aiming to create models that generalize well to unseen data. Current research emphasizes developing algorithms with improved efficiency and robustness, particularly in distributed and continual learning settings, exploring architectures like graph neural networks, transformers, and variations of gradient descent. These advancements are crucial for addressing challenges in diverse fields, including autonomous systems, healthcare, and scientific discovery, by enabling more efficient and reliable data analysis and decision-making.

Papers

June 8, 2023

PeFLL: Personalized Federated Learning by Learning to Learn
Jonathan Scott, Hossein Zakerinia, Christoph H. Lampert
LeArning Abstract Strong Generalization Learning Algorithm Learning Based Approach Non Graph Hypernetwork Baseline

June 1, 2023

An FPGA Architecture for Online Learning using the Tsetlin Machine
Samuel Prescott, Adrian Wheeldon, Rishad Shafik, Tousif Rahman, Alex Yakovlev, Ole-Christoffer Granmo
Machine Learning Model Online Learning Field Programmable Gate Array Edge Device Learning Algorithm Multi FPGA Tsetlin Machine

May 31, 2023

Active causal structure learning with advice
Davin Choo, Themis Gouleakis, Arnab Bhattacharyya
Learning Algorithm Worst Case Causal Direction Advice Quality Temporal Causal Ancestral Graph

May 24, 2023

TaxoKnow: Taxonomy as Prior Knowledge in the Loss Function of Multi-class Classification
Mohsen Pourvali, Yao Meng, Chen Sheng, Yangzhou Du
Loss Function Comprehensive Taxonomy Prior Knowledge Learning Algorithm Multi Class Classification Hierarchical Taxonomy

May 23, 2023

Statistical Indistinguishability of Learning Algorithms
Alkis Kalavasis, Amin Karbasi, Shay Moran, Grigoris Velegkas
Information Theoretic Learning Algorithm List Replicability Learning Rule Outcome Indistinguishability

May 20, 2023

(Machine) Learning to Be Like Thee? For Algorithm Education, Not Training
Susana Perez Blazquez, Inas Hipolito
LeArning Abstract Artificial Intelligence New Machine Learning Algorithm Sustainable AI Ethical Decision Making

May 11, 2023

On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm
Julien Aubert, Luc Lehéricy, Patricia Reynaud-Bouret
Estimation Task Early Stage Convergence Learning Rate Maximum Likelihood Learning Algorithm Linear Estimator Exponential Weight

May 10, 2023

Supervised learning with probabilistic morphisms and kernel mean embeddings
Hông Vân Lê
Supervised Learning Learning Algorithm Parameterized Model Statistical Learning Theory Kernel Mean Embeddings

May 3, 2023

An Adaptive Algorithm for Learning with Unknown Distribution Drift
Alessio Mazzetto, Eli Upfal
Binary Classification Learning Algorithm Linear Regression Adaptive Algorithm Distribution Drift

April 26, 2023

Regression with Sensor Data Containing Incomplete Observations
Takayuki Katsuki, Takayuki Osogami
Novel Regression Sensor Data Learning Algorithm Partial Observation Regression Problem Combining Machine Learning

March 28, 2023

Learnability, Sample Complexity, and Hypothesis Class Complexity for Regression Models
Soosan Beheshti, Mahdi Shamsi
Sample Complexity Learning Algorithm Regression Model Hypothesis Class

March 23, 2023

Une comparaison des algorithmes d'apprentissage pour la survie avec donn\'ees manquantes
Paul Dufossé, Sébastien Benzekry
Learning Algorithm Imputation Method Survival Model

February 16, 2023

Federated Learning as a Network Effects Game
Shengyuan Hu, Dung Daniel Ngo, Shuran Zheng, Virginia Smith, Zhiwei Steven Wu
Learning Algorithm Institutional Incentive Network Effect

February 9, 2023

Dual Algorithmic Reasoning
Danilo Numeroso, Davide Bacciu, Petar Veličković
Learning Algorithm Neural Algorithmic Reasoning Algorithmic Reasoning

February 8, 2023

On the Complexity of Computing G\"odel Numbers
Vasco Brattka
Complexity Matter Learning Algorithm Banach Mazur Computable Computable Learning

January 16, 2023

Hybrid quantum-classical convolutional neural networks to improve molecular protein binding affinity predictions
L. Domingo, M. Djukic, C. Johnson, F. Borondo
Quantum Machine Learning Drug Discovery Efficient Hybrid Learning Algorithm Affinity Prediction Drug Discovery Process Quantum Classical Convolutional Neural Network

January 13, 2023

A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends
Jie Gui, Tuo Chen, Jing Zhang, Qiong Cao, Zhenan Sun, Hao Luo, Dacheng Tao
Natural Language Processing Timely Survey Self Supervised Learning Financial Application Practical Algorithm Unsupervised Learning Learning Algorithm Discriminative Feature Future Trend Human Annotated Label

November 25, 2022

FedSysID: A Federated Approach to Sample-Efficient System Identification
Han Wang, Leonardo F. Toso, James Anderson
Dynamical System Learning Algorithm System Identification Dynamical Model System Heterogeneity Federated Approach

November 22, 2022

ModelDiff: A Framework for Comparing Learning Algorithms
Harshay Shah, Sung Min Park, Andrew Ilyas, Aleksander Madry
New Framework Learning Algorithm Algorithm Design Hyperparameter Configuration Input Transformation

October 6, 2022

Learning Algorithms for Intelligent Agents and Mechanisms
Jad Rahme
Reinforcement Learning Markov Decision Process Learning Algorithm Intelligent Agent Functional Mechanism Maximum Entropy Reinforcement Learning Affine Maximizer Auction