{"list":"other","total":122,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"1602.05629","title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","created":"2016-02-17","cited_by_count":7669},{"id":"1703.03400","title":"Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks","created":"2017-03-09","cited_by_count":4897},{"id":"1612.00796","title":"Overcoming catastrophic forgetting in neural networks","created":"2016-12-02","cited_by_count":4787},{"id":"1708.07747","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","created":"2017-08-25","cited_by_count":4349},{"id":"1704.04861","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","created":"2017-04-17","cited_by_count":3845},{"id":"1606.00915","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","created":"2016-06-02","cited_by_count":3241},{"id":"1812.06127","title":"Federated Optimization in Heterogeneous Networks","created":"2018-12-14","cited_by_count":2987},{"id":"1409.7495","title":"Unsupervised Domain Adaptation by Backpropagation","created":"2014-09-26","cited_by_count":1917},{"id":"1706.08840","title":"Gradient Episodic Memory for Continual Learning","created":"2017-06-26","cited_by_count":1898},{"id":"1502.02791","title":"Learning Transferable Features with Deep Adaptation Networks","created":"2015-02-10","cited_by_count":1329},{"id":"1702.05464","title":"Adversarial Discriminative Domain Adaptation","created":"2017-02-17","cited_by_count":1311},{"id":"1909.10351","title":"TinyBERT: Distilling BERT for Natural Language Understanding","created":"2019-09-23","cited_by_count":1167},{"id":"1705.08690","title":"Continual Learning with Deep Generative Replay","created":"2017-05-24","cited_by_count":1158},{"id":"1408.5882","title":"Convolutional Neural Networks for Sentence Classification","created":"2014-08-25","cited_by_count":1127},{"id":"1806.00582","title":"Federated Learning with Non-IID Data","created":"2018-06-02","cited_by_count":1108},{"id":"2112.08654","title":"Learning to Prompt for Continual Learning","created":"2021-12-16","cited_by_count":944},{"id":"1711.05769","title":"PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning","created":"2017-11-15","cited_by_count":898},{"id":"2302.00487","title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application","created":"2023-01-31","cited_by_count":872},{"id":"1801.10112","title":"Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence","created":"2018-01-30","cited_by_count":742},{"id":"1801.01423","title":"Overcoming catastrophic forgetting with hard attention to the task","created":"2018-01-04","cited_by_count":681},{"id":"1705.10467","title":"Federated Multi-Task Learning","created":"2017-05-30","cited_by_count":672},{"id":"2204.04799","title":"DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning","created":"2022-04-10","cited_by_count":642},{"id":"1903.08671","title":"Gradient based sample selection for online continual learning","created":"2019-03-20","cited_by_count":571},{"id":"2111.04263","title":"Federated Learning Based on Dynamic Regularization","created":"2021-11-08","cited_by_count":562},{"id":"1911.00222","title":"Federated Learning with Differential Privacy: Algorithms and Performance Analysis","created":"2019-11-01","cited_by_count":536},{"id":"1910.01991","title":"Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints","created":"2019-10-04","cited_by_count":503},{"id":"2004.02984","title":"MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices","created":"2020-04-06","cited_by_count":482},{"id":"2004.05785","title":"Learning under Concept Drift: A Review","created":"2020-04-13","cited_by_count":477},{"id":"2103.00710","title":"Towards Personalized Federated Learning","created":"2021-03-01","cited_by_count":464},{"id":"1903.02891","title":"Robust and Communication-Efficient Federated Learning from Non-IID Data","created":"2019-03-07","cited_by_count":419},{"id":"1804.05271","title":"Adaptive Federated Learning in Resource Constrained Edge Computing Systems","created":"2018-04-14","cited_by_count":409},{"id":"1908.04742","title":"Online Continual Learning with Maximally Interfered Retrieval","created":"2019-08-11","cited_by_count":379},{"id":"1804.08333","title":"Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge","created":"2018-04-23","cited_by_count":352},{"id":"2002.07948","title":"Personalized Federated Learning: A Meta-Learning Approach","created":"2020-02-19","cited_by_count":312},{"id":"1909.12488","title":"Improving Federated Learning Personalization via Model Agnostic Meta Learning","created":"2019-09-27","cited_by_count":269},{"id":"2101.10423","title":"Online Continual Learning in Image Classification: An Empirical Survey","created":"2021-01-25","cited_by_count":245},{"id":"2004.11791","title":"Federated learning with hierarchical clustering of local updates to improve training on non-IID data","created":"2020-04-24","cited_by_count":223},{"id":"1809.02176","title":"Multi-Adversarial Domain Adaptation","created":"2018-09-04","cited_by_count":196},{"id":"2006.06958","title":"Understanding the Role of Training Regimes in Continual Learning","created":"2020-06-12","cited_by_count":180},{"id":"1711.07027","title":"Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification","created":"2017-11-19","cited_by_count":168},{"id":"2003.03196","title":"Federated Continual Learning with Weighted Inter-client Transfer","created":"2020-03-06","cited_by_count":161},{"id":"2401.16386","title":"Continual Learning with Pre-Trained Models: A Survey","created":"2024-01-29","cited_by_count":154},{"id":"2003.08673","title":"Survey of Personalization Techniques for Federated Learning","created":"2020-03-19","cited_by_count":145},{"id":"2003.09553","title":"Adversarial Continual Learning","created":"2020-03-21","cited_by_count":142},{"id":"1911.02054","title":"Federated Adversarial Domain Adaptation","created":"2019-11-05","cited_by_count":140},{"id":"1808.04205","title":"Partial Adversarial Domain Adaptation","created":"2018-08-10","cited_by_count":127},{"id":"2203.11473","title":"Federated Class-Incremental Learning","created":"2022-03-22","cited_by_count":127},{"id":"1810.13166","title":"Don't forget, there is more than forgetting: new metrics for Continual Learning","created":"2018-10-31","cited_by_count":115},{"id":"1711.02536","title":"Few-Shot Adversarial Domain Adaptation","created":"2017-11-05","cited_by_count":111},{"id":"1412.6651","title":"Deep learning with Elastic Averaging SGD","created":"2014-12-20","cited_by_count":90},{"id":"2106.03097","title":"Preservation of the Global Knowledge by Not-True Distillation in Federated Learning","created":"2021-06-06","cited_by_count":87},{"id":"1901.09888","title":"Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System","created":"2019-01-29","cited_by_count":79},{"id":"1711.08995","title":"Unsupervised Domain Adaptation with Similarity Learning","created":"2017-11-24","cited_by_count":73},{"id":"2307.09218","title":"A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning","created":"2023-07-16","cited_by_count":69},{"id":"2303.06937","title":"TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation","created":"2023-03-13","cited_by_count":65},{"id":"2010.00243","title":"MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene Understanding","created":"2020-10-01","cited_by_count":59},{"id":"1306.6709","title":"A Survey on Metric Learning for Feature Vectors and Structured Data","created":"2013-06-28","cited_by_count":58},{"id":"2304.01663","title":"On the Stability-Plasticity Dilemma of Class-Incremental Learning","created":"2023-04-04","cited_by_count":56},{"id":"2302.13001","title":"Better Generative Replay for Continual Federated Learning","created":"2023-02-25","cited_by_count":55},{"id":"2302.00903","title":"No One Left Behind: Real-World Federated Class-Incremental Learning","created":"2023-02-02","cited_by_count":53},{"id":"2312.16475","title":"Federated Continual Learning via Knowledge Fusion: A Survey","created":"2023-12-27","cited_by_count":53},{"id":"2007.09236","title":"Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing","created":"2020-07-17","cited_by_count":52},{"id":"1912.05897","title":"HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning","created":"2019-12-12","cited_by_count":51},{"id":"2203.04640","title":"Memory Efficient Continual Learning with Transformers","created":"2022-03-09","cited_by_count":43},{"id":"2109.04197","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","created":"2021-09-09","cited_by_count":42},{"id":"2301.01299","title":"Recent Advances on Federated Learning: A Systematic Survey","created":"2023-01-03","cited_by_count":41},{"id":"2311.07784","title":"A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks","created":"2023-11-13","cited_by_count":41},{"id":"1910.09933","title":"Abnormal Client Behavior Detection in Federated Learning","created":"2019-10-22","cited_by_count":40},{"id":"2206.04055","title":"Gradient Obfuscation Gives a False Sense of Security in Federated Learning","created":"2022-06-08","cited_by_count":39},{"id":"2111.13394","title":"Non-IID data and Continual Learning processes in Federated Learning: A long road ahead","created":"2021-11-26","cited_by_count":36},{"id":"2206.00799","title":"Federated Learning under Distributed Concept Drift","created":"2022-06-01","cited_by_count":36},{"id":"2211.01572","title":"FedTP: Federated Learning by Transformer Personalization","created":"2022-11-03","cited_by_count":36},{"id":"2304.04620","title":"Federated Incremental Semantic Segmentation","created":"2023-04-10","cited_by_count":36},{"id":"2403.05890","title":"Towards Efficient Replay in Federated Incremental Learning","created":"2024-03-09","cited_by_count":33},{"id":"2110.10223","title":"A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison","created":"2021-10-19","cited_by_count":31},{"id":"2304.03626","title":"Asynchronous Federated Continual Learning","created":"2023-04-07","cited_by_count":29},{"id":"2207.07730","title":"How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition","created":"2022-07-15","cited_by_count":27},{"id":"1811.05255","title":"Deep Neural Network Concepts for Background Subtraction: A Systematic Review and Comparative Evaluation","created":"2018-11-13","cited_by_count":26},{"id":"2012.09102","title":"FedADC: Accelerated Federated Learning with Drift Control","created":"2020-12-16","cited_by_count":26},{"id":"2304.11107","title":"ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT","created":"2023-04-21","cited_by_count":26},{"id":"2401.17319","title":"Decentralized Federated Learning: A Survey on Security and Privacy","created":"2024-01-25","cited_by_count":25},{"id":"2209.15595","title":"Rethinking Data Heterogeneity in Federated Learning: Introducing a New Notion and Standard Benchmarks","created":"2022-09-30","cited_by_count":24},{"id":"2305.14657","title":"Dealing with Cross-Task Class Discrimination in Online Continual Learning","created":"2023-05-24","cited_by_count":24},{"id":"2409.01128","title":"Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning","created":"2024-09-02","cited_by_count":23},{"id":"2012.08677","title":"Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning","created":"2020-12-16","cited_by_count":22},{"id":"2208.09754","title":"FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution","created":"2022-08-20","cited_by_count":22},{"id":"2407.00113","title":"Personalized Federated Continual Learning via Multi-granularity Prompt","created":"2024-06-27","cited_by_count":20},{"id":"2304.07421","title":"Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition","created":"2023-04-14","cited_by_count":19},{"id":"2305.00380","title":"DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning","created":"2023-04-30","cited_by_count":15},{"id":"2308.03374","title":"Heterogeneous Forgetting Compensation for Class-Incremental Learning","created":"2023-08-07","cited_by_count":15},{"id":"2109.00151","title":"Asynchronous Federated Learning for Sensor Data with Concept Drift","created":"2021-09-01","cited_by_count":14},{"id":"2302.03662","title":"Federated Learning with Regularized Client Participation","created":"2023-02-07","cited_by_count":14},{"id":"2310.14906","title":"DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset","created":"2023-10-20","cited_by_count":14},{"id":"1710.02030","title":"McDiarmid Drift Detection Methods for Evolving Data Streams","created":"2017-10-05","cited_by_count":13},{"id":"2110.09695","title":"Tackling Dynamics in Federated Incremental Learning with Variational Embedding Rehearsal","created":"2021-10-19","cited_by_count":11},{"id":"2411.13740","title":"Federated Continual Learning for Edge-AI: A Comprehensive Survey","created":"2024-11-20","cited_by_count":11},{"id":"1709.02457","title":"Reservoir of Diverse Adaptive Learners and Stacking Fast Hoeffding Drift Detection Methods for Evolving Data Streams","created":"2017-09-07","cited_by_count":10},{"id":"1909.02993","title":"SocNav1: A Dataset to Benchmark and Learn Social Navigation Conventions","created":"2019-09-06","cited_by_count":10}],"next_cursor":"100"}