We are the Distributed Learning Systems Lab at the Distributed Systems Section, EWI faculty, TU Delft. We working on a wide variety of research problems in distributed machine learning systems, and developing cutting edge AI technology for industry.

Our lab is supported by TU Delft, Aegon, ABB Research, Swiss National Science Foundation (SNSF), and Dutch National Science Foundation (NWO).

News

[10/22] Our paper, “Robust Learning via Golden Symmetric Loss of (un)Trusted Labels " , is accpted in SIAM SDM 23

[10/22] Our paper, “FedKNow:Federated Continual Learning with Signature Task Knowledge Integration at Edge" , is accpted in IEEE ICDE 23

[10/22] Our paper, “Permutation-Invariant Tabular Data Synthesis " , is accpted in IEEE Bigdata 22

[09/22] Our paper, “Trusted Loss Correction for Noisy Multi-Label Learning" , is accpted in ACML 22

[09/22] Our paper, “Multi Label Loss Correction against Missing and Corrupted Labels" , is accpted in ACML 22

[08/22] Our paper, “FreezOff: A Middleware for Heterogeneous Federated Learning Systems” , is accpted in Middleware 22

[08/22] Our paper, “Community-based Approach to Gender-Constrained Influence Maximization" , is accpted in CIKM 22

[06/22] Our paper, “AGIC: Approximate Gradient Inversion Attack on Federated Learning" , is accpted in SRDS22

[06/22] Our paper, “Performance Modeling for Short-Term Cache Allocation" , is accepted at ACM ICPP 2022

[05/22] Lydia receives a NWO Preserpectief grant, a large scaled multi-disciplinary project.

[04/22] Lydia will serve TPC SoCC 22.

[04/22] Our paper, “LegoDN" , is awareded with Runner-up Community Award at MobiCom

[03/22] Our paper, “EdggeTune:Inference-Aware Multi-Parameter Tuning" , is accepted at ACM Middlewareware22

[12/21] Our paper, “Lightweight and Accurate DNN-based Anomaly Detection at Edge" , is accpted in IEEE Transactions on Parallel and Distribution Computing

[12/21] Our paper, “EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources" , is accpted in IEEE INFOCOM22

[11/21] Our paper, “Locality Sensitive Hash Aggregated Nonlinear Neighborhood MatrixFactorization for Online Sparse Big Data Analysis" , is accpted in ACM Transactions on Data Science

[10/21] Lydia will serve TPC CCGRID22 .

[09/21] Our paper, CTAB-GAN: Effective Table Data Synthesizing , is accpted in ACML21

[09/21] Our paper, QActor: On-line Active Learning for Noisy Labeled Stream Data , is accpted in ACML21

[08/21] Our paper, LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision , is accepted in MobiCom21

[08/21] Our paper, Federated Learning with Heterogeneity-Aware Probabilistic Synchronous Parallel on Edge , is accepted in IEEE Transactions on Service Computing

[08/21] Our paper, Disparity seeding , is accepted in CIKM21

[07/21] Lydia will serve TPC co-chair of BDCAT21 .

[08/21] Lydia will serve TPC Sigmetrics21 .

[07/21] The Generatrix team enters the semi-final of The European Social Innovation Competition !

[07/21] We graduate 13 bachelor students on broad topics of synthesizing comics, privacy preserving time-series synthesizing, and robust multi-label learning.

[07/21] Our paper on differential privacy for sparse tensor factorization is accepted in IEEE Transactions on Industrial Informatics