Linear Algorithms for Online Multitask Classification

No abstract is available for this paper.

• Publication year

  2010

• Venue

  Annual Conference Computational Learning Theory

• Publication date

  2010-03-01

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.5555/1756006.1953026
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Online Multi-task Learning with Hard Constraints

  2009cited by this paper
• Predicting the Labelling of a Graph via Minimum $p$-Seminorm Interpolation

  2009cited by this paper
• Applications of strong convexity--strong smoothness duality to learning with matrices

  2009cited by this paper
• On the duality of strong convexity and strong smoothness : Learning applications and matrix regularization

  2009cited by this paper
• Matrix regularization techniques for online multitask learning

  2008cited by this paper
• Clustered Multi-Task Learning: A Convex Formulation

  2008cited by this paper
• An RKHS for multi-view learning and manifold co-regularization

  2008cited by this paper
• Large Deviations of Vector-valued Martingales in 2-Smooth Normed Spaces

  2008influential reference
• Online Learning of Multiple Tasks with a Shared Loss

  2007cited by this paper
• A Spectral Regularization Framework for Multi-Task Structure Learning

  2007cited by this paper
• Multi-view Regression Via Canonical Correlation Analysis

  2007cited by this paper
• Multitask Learning with Expert Advice

  2007cited by this paper
• The Rademacher Complexity of Co-Regularized Kernel Classes

  2007cited by this paper
• Winnowing subspaces

  2007influential reference
• Efficient co-regularised least squares regression

  2006cited by this paper
• Bounds for Linear Multi-Task Learning

  2006cited by this paper
• Prediction, learning, and games

  2006cited by this paper
• Handbook of Linear Algebra

  2006cited by this paper
• Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection

  2005influential reference
• A Co-Regularization Approach to Semi-supervised Learning with Multiple Views

  2005cited by this paper
• Learning Multiple Tasks with Kernel Methods

  2005cited by this paper
• A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data

  2005cited by this paper
• Online learning over graphs

  2005cited by this paper
• Mirror descent and nonlinear projected subgradient methods for convex optimization

  2003cited by this paper
• A Second-Order Perceptron Algorithm

  2002cited by this paper
• Regularization Networks and Support Vector Machines

  2000cited by this paper
• Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions

  1999cited by this paper
• The Robustness of the p-Norm Algorithms

  1999cited by this paper
• Matrix Differential Calculus with Applications in Statistics and Econometrics (Revised Edition)

  1999cited by this paper
• Large Margin Classification Using the Perceptron Algorithm

  1998cited by this paper
• General Convergence Results for Linear Discriminant Updates

  1997influential reference
• Relative Loss Bounds for Multidimensional Regression Problems

  1997cited by this paper
• The Convex Analysis of Unitarily Invariant Matrix Functions

  1995cited by this paper
• Topics in Matrix Analysis

  1991cited by this paper
• Mistake bounds and logarithmic linear-threshold learning algorithms

  1990cited by this paper
• Matrix Differential Calculus with Applications

  1988cited by this paper
• Matrix analysis

  1985cited by this paper
• Problem Complexity and Method Efficiency in Optimization

  1983cited by this paper

• Towards Understanding the Benefit of Multitask Representation Learning in Decision Process

  2025cites this paper
• Enhancing Knowledge Reusability: A Distributed Multitask Machine Learning Approach

  2025influential citation
• Multi-Task Dynamic Pricing in Credit Market with Contextual Information

  2024cites this paper
• Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data

  2024cites this paper
• A survey on kernel-based multi-task learning

  2024cites this paper
• Optimistic Rates for Multi-Task Representation Learning

  2023cites this paper
• Multi-task Representation Learning for Pure Exploration in Linear Bandits

  2023cites this paper
• Delayed Bandits: When Do Intermediate Observations Help?

  2023cites this paper
• Multitask Online Learning: Listen to the Neighborhood Buzz

  2023cites this paper
• A Theory of Multimodal Learning

  2023cites this paper
• Online Multi-Task Learning with Recursive Least Squares and Recursive Kernel Methods

  2023cites this paper
• Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning

  2023influential citation
• Provable General Function Class Representation Learning in Multitask Bandits and MDPs

  2022cites this paper
• Nearly Minimax Algorithms for Linear Bandits with Shared Representation

  2022cites this paper
• Provable and Efficient Continual Representation Learning

  2022cites this paper
• Trace norm regularization for multi-task learning with scarce data

  2022cites this paper
• On the Sample Complexity of Representation Learning in Multi-task Bandits with Global and Local structure

  2022cites this paper
• Towards Sample-efficient Overparameterized Meta-learning

  2022cites this paper
• A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty

  2022cites this paper
• Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness

  2022cites this paper
• AdaTask: Adaptive Multitask Online Learning

  2022cites this paper
• Multi-Environment Meta-Learning in Stochastic Linear Bandits

  2022cites this paper
• Active Multitask Learning with Committees

  2021cites this paper
• Multi-Trigger-Key: Toward Multi-Task Privacy Preserving in Deep Learning

  2021cites this paper
• Assessment of Parkinson’s Disease Severity From Videos Using Deep Architectures

  2021cites this paper
• Learning Collections of Functions

  2021cites this paper
• On the Power of Multitask Representation Learning in Linear MDP

  2021cites this paper
• What Makes Multimodal Learning Better than Single (Provably)

  2021cites this paper
• Boosting a Model Zoo for Multi-Task and Continual Learning

  2021cites this paper
• Multitask Online Mirror Descent

  2021influential citation
• Sample Efficient Subspace-Based Representations for Nonlinear Meta-Learning

  2021cites this paper
• A Gang of Adversarial Bandits

  2021cites this paper
• Model Zoo: A Growing Brain That Learns Continually

  2021cites this paper
• AutoTL: Learning to Transfer Automatically

  2020cites this paper
• Transitive Transfer Learning

  2020cites this paper
• Transfer Learning

  2020cites this paper
• Heterogeneous Transfer Learning

  2020cites this paper
• Lifelong Machine Learning

  2020cites this paper
• Transfer Learning in Computer Vision

  2020cites this paper
• Relation-Based Transfer Learning

  2020cites this paper
• Introduction

  2020cites this paper
• Instance-Based Transfer Learning

  2020cites this paper
• Transfer Learning Theory

  2020cites this paper
• Transfer Learning in Bioinformatics

  2020cites this paper
• Index

  2020cites this paper
• Preface

  2020cites this paper
• Transfer Learning in Urban Computing

  2020cites this paper
• Feature-Based Transfer Learning

  2020cites this paper
• Transfer Learning in Natural Language Processing

  2020cites this paper
• Multi-task Learning

  2020cites this paper
• Model-Based Transfer Learning

  2020cites this paper
• Transfer Learning in Reinforcement Learning

  2020cites this paper
• Privacy-Preserving Transfer Learning

  2020cites this paper
• Transfer Learning in Dialogue Systems

  2020cites this paper
• Impact of Representation Learning in Linear Bandits

  2020cites this paper
• Transfer Learning in Recommender Systems

  2020cites this paper
• Provable Benefits of Representation Learning in Linear Bandits

  2020cites this paper
• The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning

  2020cites this paper
• Online Multitask Learning with Long-Term Memory

  2020cites this paper
• Online Parameter-Free Learning of Multiple Low Variance Tasks

  2020influential citation
• On the Theory of Transfer Learning: The Importance of Task Diversity

  2020cites this paper
• Meta-learning with Stochastic Linear Bandits

  2020influential citation
• Research on Face Attribute Recognition Based on Multi-task CNN Network

  2020cites this paper
• Few-Shot Learning

  2020cites this paper
• Inducing Optimal Attribute Representations for Conditional GANs

  2020influential citation
• Sharing Knowledge in Multi-Task Deep Reinforcement Learning

  2020cites this paper
• Multi-Lingual Dependency Parsing: Word Representation and Joint Training for Syntactic Analysis. (Parsing en Dépendances Multilingue: Représentation de Mots et Apprentissage Joint pour l'Analyse Syntaxique)

  2019cites this paper
• A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multitask Learning Algorithms (OMTL)

  2019influential citation
• Weighted feature-task-aware regularization learner for multitask learning

  2019cites this paper
• Provable Guarantees for Gradient-Based Meta-Learning

  2019cites this paper
• Lifelong Optimization with Low Regret

  2019cites this paper
• Cyber-Typhon: An Online Multi-task Anomaly Detection Framework

  2019cites this paper
• Phylogenic Multi-Lingual Dependency Parsing

  2019cites this paper
• Transfer Learning in Natural Language Processing

  2019cites this paper
• Cross-Lingual Word Embeddings

  2019cites this paper
• Kernel-Based Efficient Lifelong Learning Algorithm

  2019cites this paper
• Concluding Remarks

  2019cites this paper
• Collaborative online ranking algorithms for multitask learning

  2019cites this paper
• Asynchronous Online Federated Learning for Edge Devices

  2019cites this paper
• Learning Transferable Knowledge Through Embedding Spaces

  2019cites this paper
• Acquiring Domain Knowledge for Cardiotocography: A Deep Learning Approach

  2019cites this paper
• Asynchronous Online Federated Learning for Edge Devices with Non-IID Data

  2019cites this paper
• Dynamic Structure Embedded Online Multiple-Output Regression for Streaming Data

  2019cites this paper
• Localized Multiple Kernel Learning With Dynamical Clustering and Matrix Regularization

  2018cites this paper
• On Similarity Prediction and Pairwise Clustering

  2018cites this paper
• Incremental Learning-to-Learn with Statistical Guarantees

  2018cites this paper
• Towards more Reliable Transfer Learning

  2018cites this paper
• Distributed multi-task classification: a decentralized online learning approach

  2018influential citation
• An Overview of Multi-task Learning

  2018cites this paper
• Discovering the structure of natural language sentences by semi-supervised methods

  2018cites this paper
• Online Learning: A Comprehensive Survey

  2018cites this paper
• MOLESTRA: A Multi-Task Learning Approach for Real-Time Big Data Analytics

  2018cites this paper
• Multi-Task Learning with Second-Order Gradient Information

  2018cites this paper
• Preference learning for machine translation

  2018cites this paper
• Learning To Learn Around A Common Mean

  2018cites this paper
• Task and Instance Quadratic Ordering for Active Online Multitask Learning

  2018cites this paper
• Adversarial Transfer Learning

  2018cites this paper
• STARS: Soft Multi-Task Learning for Activity Recognition from Multi-Modal Sensor Data

  2018cites this paper
• Robust Online Multi-Task Learning with Correlative and Personalized Structures

  2017cites this paper
• An Overview of Multi-Task Learning in Deep Neural Networks

  2017cites this paper