NIPS Randomized Algorithms - Francis Bach: Minimizing finite sums with stochastic average gradient
NIPS Randomized Algorithms - Francis Bach: Minimizing finite sums with stochastic average gradient
|
Yükleniyor...
 Hızlı erişim için Tubidy'yi favorilerinize ekleyin.
Lütfen bekleyiniz...
Type
Size

 İlgili Videolar

NIPS Randomized Algorithms - Francis Bach: Minimizing finite sums with stochastic average gradient

NIPS Randomized Algorithms - Francis Bach: Minimizing finite sums with stochastic average gradient

|
NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach (Submodularity: Discrete to Continuous)

NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach (Submodularity: Discrete to Continuous)

|
Averaged Stochastic Gradient Descent on Riemannian Manifolds

Averaged Stochastic Gradient Descent on Riemannian Manifolds

|
Francis Bach - Conditional Gradients Everywhere - invited talk

Francis Bach - Conditional Gradients Everywhere - invited talk

|
[W13-5] SAG and SAGA

[W13-5] SAG and SAGA

|
IDSS Distinguished Seminar Series, October 16, 2018 | Francis Bach

IDSS Distinguished Seminar Series, October 16, 2018 | Francis Bach

|
Francis Bach at France is AI 2017: Optimization for machine learning

Francis Bach at France is AI 2017: Optimization for machine learning

|
Data Science @ ESIEE Paris - Francis Bach

Data Science @ ESIEE Paris - Francis Bach

|
Stochastic Quasi-Gradient Methods: Variance Reduction via Jacobian Sketching

Stochastic Quasi-Gradient Methods: Variance Reduction via Jacobian Sketching

|
6.4 SGD and SVRG

6.4 SGD and SVRG

|
Mark Schmidt - Faster Algorithms for Deep Learning?

Mark Schmidt - Faster Algorithms for Deep Learning?

|
Iterate Averaging as Regularization for Stochastic Gradient Descent

Iterate Averaging as Regularization for Stochastic Gradient Descent

|
NIPS Randomized Algorithms - Michael Mahoney: Randomized Numerical Linear Algebra

NIPS Randomized Algorithms - Michael Mahoney: Randomized Numerical Linear Algebra

|
Research in Focus: Large-Scale Machine Learning

Research in Focus: Large-Scale Machine Learning

|
Seminar on Applied Geometry and Algebra (SIAM SAGA): Avi Wigderson

Seminar on Applied Geometry and Algebra (SIAM SAGA): Avi Wigderson

|
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization

Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization

|
Tight Complexity Bounds for Composite Optimization

Tight Complexity Bounds for Composite Optimization

|
Structured Sparsity-Inducing Norms Through Submodular Functions

Structured Sparsity-Inducing Norms Through Submodular Functions

|
[PURDUE MLSS] Large-scale Machine Learning and Stochastic Algorithms by Leon Bottou (Part 1/6)

[PURDUE MLSS] Large-scale Machine Learning and Stochastic Algorithms by Leon Bottou (Part 1/6)

|
06 Randomized algorithms 01 Randomized algorithms intro

06 Randomized algorithms 01 Randomized algorithms intro

|
Copyright. All rights reserved © 2025
Rosebank, Johannesburg, South Africa

Favorilere Ekle