Peter Richtarik

1:29:34

Vol. 4: The role of local training in federated learning

0:06:32

High Order Tensor Formulation for Convolutional Sparse Coding

0:15:00

TMLR: Optimal Client Sampling for Federated Learning

0:01:26

Odborný výcvik 3.D

0:04:14

Konfigurácia routra Mikro-Tik

0:55:15

#OR58: Peter Richtárik Plenary Talk, 'Introduction to Big Data Optimisation'

1:13:01

OWOS: Peter Richtárik - 'Second Order Methods and Randomness'

6:11:51

CrossFL-2022: Workshop on Cross-Community Federated Learning: Algorithms, Systems and Co-designs

0:37:48

Generative Adversarial Models for Privacy and Fairness

0:11:15

NSDI '21 - Scaling Distributed Machine Learning with In-Network Aggregation

0:37:10

Towards “One-Shot” Privacy Auditing and Estimation

0:30:42

Google Workshop on Federated Learning and Analytics: Breakout Session Closing Summaries

0:22:01

Survey on Privacy/Security in FL

0:11:22

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints

0:10:08

The Skellam Mechanism for Differentially Private Federated Learning

0:43:45

Federated Heavy Hitters Discovery with Differential Privacy

0:45:58

Peter Wonka -- Semantic Image Editing using GANs

0:14:52

OM PriCon2020: OpenMined Advances and Open Problems in Federated Learning - Peter Kairouz

0:59:53

Google Keynote: Federated Learning & Federated Analytics-Research, Applications, & System Challenges

1:24:25

P. Richtárik 'Distributed Second Order Methods with Fast Rates and Compressed Communication'

1:13:10

FLOW Seminar #14: Peter Kairouz (Google) Federated Analytics

0:12:01

[2B] Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy...

1:00:22

Optimization

0:47:09

Tutorial: Integer Programming for Visual Computing - Part 1 / 5