Peter Richtarik

0:47:09

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

1:03:23

Optimization in Theory and Practice

0:00:55

Peter Košťál a Michal Pokorný Biketrial - Drahovské vrtochy 2014

0:04:51

Primal/Dual Descent Methods for Dynamics Submission Video

0:34:58

Peter Kairouz - Challenges and Opportunities in Differentially Private Federated Learning

1:08:52

OWOS: Guoyin Li - 'Estimating the Exponents of KL Inequality & Error Bounds for Optimization Models'

0:02:51

Anytime Planning for Decentralized Multi-Robot Active Information Gathering

1:08:20

FLOW Seminar #34: Konstantin Mishchenko (KAUST) Proximal and Federated Random Reshuffling

0:31:24

Deep network pruning: a stochastic proximal method for non smooth regularized optimization

2:13:47

Coding & Optimization (Full Session)

1:03:56

Machine Learning NeEDS Mathematical Optimization with Dr Coralia Cartis

0:05:00

Quantum Permutation Synchronization [CVPR 2021]

0:27:32

Talk #3: Revisiting Randomized Gossip Algorithms

0:06:11

Regularised Tomographic reconstruction using Primal Dual Hybrid Gradient algorithm with CIL 19.10

0:43:05

[SPCL_Bcast] A Paradigm Shift to Second Order Methods for Machine Learning

1:36:15

PPAI21 - Tutorial by Brendan McMahan, Kallista Bonawitz, and Peter Kairouz

1:06:39

Day 2 Lightning Talks: Privacy & Security

0:01:01

Robust Reference-Based Super-Resolution With Similarity-Aware Deformable Convolution

0:01:52

Inexact Block Coordinate Descent Algorithms for Nonsmooth Nonconvex Optimization

0:23:35

SDS|2015: Martin Jaggi on Distributed Machine Learning

0:33:43

DLVC - 41 - Generative Adversarial Networks - Part 4 / X

0:58:33

Ali Jadbabaie | Optimization Theory and Machine Learning Practice: Minding the Gap

1:06:41

Stochastic Second Order Optimization Methods I

0:03:02

E31 Dmitry Kovalev A Linearly Convergent Algorithm for Decentralized Optimization Sending Less