Cover Image

Memory-efficient Continual Learning with Prototypical Exemplar Condensation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nguyen, Minh-Duong, Dao, Thien-Thanh, Nguyen, Le-Tuan, Le, Dung D., Wong, Kok-Seng
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence 68T05 I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Prompting to Preference Optimization: A Comparative Study of LLM-based Automated Essay Scoring
by: Nguyen, Minh Hoang, et al.
Published: (2026)

Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition
by: Bouchabou, Damien, et al.
Published: (2024)

Fine-Tuning Regimes Define Distinct Continual Learning Problems
by: Iordache, Paul-Tiberiu, et al.
Published: (2026)

Temporal Taskification in Streaming Continual Learning: A Source of Evaluation Instability
by: Filat, Nicolae, et al.
Published: (2026)

More at Stake: How Payoff and Language Shape LLM Agent Strategies in Cooperation Dilemmas
by: Huynh, Trung-Kiet, et al.
Published: (2026)

Co-NAML-LSTUR: A Combined Model with Attentive Multi-View Learning and Long- and Short-term User Representations for News Recommendation
by: Nguyen, Minh Hoang, et al.
Published: (2025)

Reinforcement Learning for Stock Transactions
by: Zhou, Ziyi, et al.
Published: (2025)

Don't Look Back in Anger: MAGIC Net for Streaming Continual Learning with Temporal Dependence
by: Giannini, Federico, et al.
Published: (2026)

Data-Driven Preference Sampling for Pareto Front Learning
by: Ye, Rongguang, et al.
Published: (2024)

Feature-aware Modulation for Learning from Temporal Tabular Data
by: Cai, Hao-Run, et al.
Published: (2025)

RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
by: Hisaki, Yukinari, et al.
Published: (2024)

Quantum Machine Learning for Predicting Anastomotic Leak: A Clinical Study
by: Novák, Vojtěch, et al.
Published: (2025)

A Practical Guide to Streaming Continual Learning
by: Cossu, Andrea, et al.
Published: (2026)

Improving Generalization in Heterogeneous Federated Continual Learning via Spatio-Temporal Gradient Matching with Prototypical Coreset
by: Nguyen, Minh-Duong, et al.
Published: (2025)

Contrastive Mutual Information Learning: Toward Robust Representations without Positive-Pair Augmentations
by: Livne, Micha
Published: (2025)

Evaluating Model-Agnostic Meta-Learning on MetaWorld ML10 Benchmark: Fast Adaptation in Robotic Manipulation Tasks
by: Atamuradov, Sanjar
Published: (2025)

Contrastive MIM: A Contrastive Mutual Information Framework for Unified Generative and Discriminative Representation Learning
by: Livne, Micha
Published: (2025)

An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
by: Saini, Saurabh, et al.
Published: (2026)

MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence
by: Giannini, Federico, et al.
Published: (2026)

Retrieval-Augmented Memory for Online Learning
by: Du, Wenzhang
Published: (2025)

Human-Aligned Skill Discovery: Balancing Behaviour Exploration and Alignment
by: Hussonnois, Maxence, et al.
Published: (2025)

Your Data, My Model: Learning Who Really Helps in Federated Learning
by: Abdurakhmanova, Shamsiiat, et al.
Published: (2024)

Adaptive Weighting in Knowledge Distillation: An Axiomatic Framework for Multi-Scale Teacher Ensemble Optimization
by: Flouro, Aaron R., et al.
Published: (2026)

Effects of Initialization Biases on Deep Neural Network Training Dynamics
by: Pellegrino, Nicholas, et al.
Published: (2025)

When Redundancy Matters: Machine Teaching of Representations
by: Ferri, Cèsar, et al.
Published: (2024)

Data structure > labels? Unsupervised heuristics for SVM hyperparameter estimation
by: Cholewa, Michał, et al.
Published: (2021)

Understanding the Limits of Deep Tabular Methods with Temporal Shift
by: Cai, Hao-Run, et al.
Published: (2025)

Multi-Teacher Ensemble Distillation: A Mathematical Framework for Probability-Domain Knowledge Aggregation
by: Flouro, Aaron R., et al.
Published: (2026)

Grammar-based evolutionary approach for automated workflow composition with domain-specific operators and ensemble diversity
by: Barbudo, Rafael, et al.
Published: (2024)

Adaptive Exploration for Latent-State Bandits
by: Jin, Jikai, et al.
Published: (2026)

Hard Samples, Bad Labels: Robust Loss Functions That Know When to Back Off
by: Pellegrino, Nicholas, et al.
Published: (2025)

Nonlinear Data Integration via Kernel Methods for Data Collaboration Analysis
by: Suetake, Yamato, et al.
Published: (2026)

Adaptive Bernstein Change Detector for High-Dimensional Data Streams
by: Heyden, Marco, et al.
Published: (2023)

Correction and Corruption: A Two-Rate View of Error Flow in LLM Protocols
by: Reitich, Fernando
Published: (2026)

Distinguished In Uniform: Self Attention Vs. Virtual Nodes
by: Rosenbluth, Eran, et al.
Published: (2024)

Federated Learning based on Self-Evolving Gaussian Clustering
by: Ožbot, Miha, et al.
Published: (2025)

Optimizing Inference in Transformer-Based Models: A Multi-Method Benchmark
by: Ho, Siu Hang, et al.
Published: (2025)

Multi-Scale Graph Learning for Anti-Sparse Downscaling
by: Fan, Yingda, et al.
Published: (2025)

Step-E: A Differentiable Data Cleaning Framework for Robust Learning with Noisy Labels
by: Du, Wenzhang
Published: (2025)

cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series
by: Giannini, Federico, et al.
Published: (2026)